| VARIABLE | MEAN | SD |
|---|---|---|
| **DEPENDENT VARIABLE** | ||
| Median House Value | $66287.73 | $60006.08 |
| **PREDICTORS** | ||
| # Households in Poverty | 189.77 | 164.32 |
| % Individuals w/ Bachelor's Degrees or Higher | 16.08% | 17.77% |
| % Vacant Houses | 11.29% | 9.63% |
| % Single House Units | 9.23% | 13.25% |
Homework 1: Using OLS Regression to Predict Median House Values in Philadelphia
1. INTRODUCTION
- INSTRUCTIONS: State the problem and the setting of the analysis (i.e., Philadelphia).
- INSTRUCTIONS: Present either a brief review of the literature (use Google Scholar) or simply speculate as to why the predictors we’re using might be related with the response variable.
The task is to explore the relationship between median house values and various neighborhood characteristics using Philadelphia data at the Census block group level. (Literature review on impact predictors have on response variable)
2. METHODS
a) Data Cleaning
The original Philadelphia block group data set had 1,816 observations. The data was cleaned by removing the following block groups:
1) Block groups where population < 40
2) Block groups where there are no housing units
3) Block groups where the median house value is lower than $10,000
4) One North Philadelphia block group which had a very high median house value (over 800,000 USD) and a very low median household income (less than 8,000 USD)The final data set that was tested consists of 1,720 block groups.
b) Exploratory Data Analysis
Our purpose is to examine the summary statistics and distributions of the data. To achieve this, we start by creating histograms of each of the predictors to check for normal distribution and examining significant outliers.
As part of our exploratory data analysis, we also examine the correlations between the predictors to assess relationships among independent variables.
A correlation coefficient is a statistical measure that quantifies the strength and direction of the linear relationship between two variables. The sample correlation coefficient r is calculated as:
\[ r = \frac{\sum (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum (x_i - \bar{x})^2 \sum (y_i - \bar{y})^2}} \] where x_i and y_i represent individual observations of the sample data and {x} and {y} are the sample means.
The value of correlation coefficient r ranges from −1 to +1. A value of r = +1 indicates a perfect positive linear relationship, in that all (x_i, y_i) pairs lie on a line with a positive slope, and r = −1 indicates a perfect negative linear relationship, in that all (x_i, y_i) pairs lie on a line with a negative slope. A value of r = 0 indicates a lack of linear relationship between the variables.
c) Multiple Regression Analysis
- INSTRUCTIONS: State the equation for y for this problem.
- In your report, instead of y and x1…xk, fill in the actual variable names (as in the regression example given above). Be sure to mention what βi’s and ε are as well. If the variables are log transformed, be sure to indicate that in the formulas.
- INSTRUCTIONS: State and explain regression assumptions (e.g., linearity; independence of observations; normality of residuals; homoscedasticity; no multicollinearity).
- INSTRUCTIONS: Mention the parameters that need to be estimated in multiple regression (σ2, β0 ,…, βk). State what σ2 is.
- INSTRUCTIONS: Talk about the way of estimating the parameters. (Hint: present the equation on the slide ‘β Coefficient Estimation – Least Squares’ for multiple regression and briefly discuss what the equation does).
- INSTRUCTIONS: Talk about the coefficient of multiple determination R2, and the adjusted R2. Present and explain the relevant formulas and all the terms that are used in the formulas.
- INSTRUCTIONS: State the hypotheses you test. Specifically, talk about the F-ratio and the H0 and Ha associated with it, as well as the hypotheses you test about each of the individual βi’s (again, state H0 and Ha).
Multiple linear regression is a method used to examine the relationship between a dependent variable and one or more explanatory variables. In other words, this method visualizes the relationship between a dependent variable Y and a set of predictors X_1, X_2, …, X_k. Regression is used to predict the dependent variable based on the predictors, to test hypotheses about relationships between variables, and to understand which predictors are important in explaining the dependent variable. Each independent variable has its own slope coefficient, which indicates the relationship of that particular predictor with the dependent variable while controlling for all other independent variables in the regression. However, it is important to note that if an explanatory variable is a significant predictor of the dependent variable this does not imply causation. The formula with appropriate variables from our task is as followed:
\[ \log(\text{Median Home Value}) = \beta_0 + \log\beta_1(\text{Poverty}) + \beta_2(\text{Education}) + \beta_3(\text{Vacancy}) + \beta_4(\text{Single Units}) + \varepsilon \] In this equation, β0 is the intercept, representing the expected value of median house value when all predictors equal zero. The coefficients βi (for i=1,2,…,k) are the partial regression coefficients, indicating the change in median house value associated with a one-unit increase in predictor i, holding all other predictors constant. The variable ε is the residual or random error term in the model. Without ε, any observed pair (x,y) would fall exactly on the line y=β0+β1x_1 called the true (or population) regression line. The inclusion of the random error term ε allows (x,y) observations to fall either above the true regression line (when ε>0) or below the line (when ε<0). The points (x1,y1),(x2,y2),…,(xn,yn) resulting from n independent observations will then be scattered about the true regression line.
d) Additional Analyses
- INSTRUCTIONS: Talk about stepwise regression – discuss what it does and its limitations.
- INSTRUCTIONS: Talk about k-fold cross-validation (mentioning that k = 5) – discuss what it is used for, describe how it is operationalized and mention that the RMSE is used to compare models (explain what the RMSE is and how it is calculated, presenting and describing any relevant formulas).
e) Software
- INSTRUCTIONS: State that you’re using R for your data analysis.
All analyses were conducted in R Studio 2025.09.1+401 using R language version 4.5.1.
3. RESULTS
Exploratory Results
Summary Statistics
- INSTRUCTIONS: Present and briefly talk about the table with summary statistics which includes the dependent variable and the predictors (i.e., mean, standard deviation).
All the variables’ means and standard deviations are close together, with the bachelor’s degree variable having a standard deviation higher than the mean. The data could be very inconsistent, because the standard deviations are as high or higher than the means this indicates the values fluctuate; this suggests there’s a significant disparity in house values in the area. The average is influenced by outliers, so the data is dispersed far from the mean, it could be that the median would be best representative of the typical value in the area. It’s possible the distribution might not be a normal, symmetrical bell curve.
Histograms and Logarithmic Transformations
- INSTRUCTIONS: State whether the variables are normal before and after the logarithmic transformation.
- Present the histograms of the original variables alongside the histograms of the log-transformed variables, and clearly state whether you’re using the log-transformed or original variable in your regression.
- State that the other regression assumptions will be examined in a separate section below (Regression Assumption Checks).
Other regression assumptions will be examined in a separate section below in “Regression Assumption Checks”.
Choropleth Maps
- INSTRUCTIONS: Present the choropleth maps of the dependent variable and the predictors.
- Refer to the maps in the text, and talk about the following: Which maps look similar? Which maps look different? That is, which predictors do you expect to be strongly associated with the dependent variable based on the visualization? Also, given your examination of the maps, are there any predictors that you think will be strongly inter-correlated? That is, do you expect severe multicollinearity to be an issue here? Discuss this in a paragraph.
Reading layer `RegressionData' from data source
`/root/spatial-statistics/HW1_OLS_Regression/data/RegressionData.shp'
using driver `ESRI Shapefile'
Simple feature collection with 1720 features and 13 fields
Geometry type: POLYGON
Dimension: XY
Bounding box: xmin: 2660605 ymin: 207610.6 xmax: 2750171 ymax: 304858.8
CRS: NA
House values are much higher in northwest Philadelphia, likely because it’s a suburb and encompasses Wissahickon Valley Park’s vast green space, and proximity to greenery tends to increase property values in neighborhoods.
Looks like there are more vacant units clustered in northern Philadelphia, which many local Philadelphians anecdotally state possesses high rates of low-income populations and communities in poverty. Can see a similar gradient, although less stark, in southwest Philadelphia and the Mantua neighborhood in west Philadelphia.
Less rowhouse architecture in the periphery of Philadelphia, which seems to spatially coincide with the visual that displays the natural log of median household values. The city is majorly connected rowhouses or apartment buildings.
High concentrations of those with a bachelor’s degree or more residing in Center City, Wissahickon, and University City areas, as well as the northwestern part of the county on the west side of the Schuylkill River that leads toward Bryn Mawr.
Many households in poverty seem to encompass areas that don’t have detached single-family homes. Lots of noticeable clusters in north, west, and south Philadelphia.
Correlation Matrix
- INSTRUCTIONS: Present the correlation matrix of the predictors which you obtained from R.
- Talk about whether the correlation matrix shows that there is severe multicollinearity.
- Does the correlation matrix support your conclusions based on your visual comparison of predictor maps?
LNPCTBACHMORE LNNBELPOV100 LNPCTVACANT LNPCTSINGLES
LNPCTBACHMORE 1.00000000 -0.2956891 -0.3586040 0.06331024
LNNBELPOV100 -0.29568910 1.0000000 0.3813548 -0.10431608
LNPCTVACANT -0.35860403 0.3813548 1.0000000 -0.08102890
LNPCTSINGLES 0.06331024 -0.1043161 -0.0810289 1.00000000Warning: `aes_string()` was deprecated in ggplot2 3.0.0.
ℹ Please use tidy evaluation idioms with `aes()`.
ℹ See also `vignette("ggplot2-in-packages")` for more information.
ℹ The deprecated feature was likely used in the ggcorrplot package.
Please report the issue at <https://github.com/kassambara/ggcorrplot/issues>.
Observations:
LNPCTBACHMORE = 0.4818251 (percent bachelor’s degrees have a weak positive correlation with median household value)
LNNBELPOV100 = -0.3255461 (number households in poverty have a weak negative correlation with median household value)
LNPCTVACANT = -0.3205985 (percent vacant units have a weak negative correlation with median household value)
LNPCTSINGLES = 0.01660472 (percent detached single-family homes have a weak positive correlation with median household value).
0 ≤ | r | ≤ ±0.5: weak correlation
±0.5 < | r | < ±0.8: moderate correlation
±0.8 ≤ | r | < ±1: strong correlation
Regression Results
- INSTRUCTIONS: Present the regression output from R. Be sure that your output presents the parameter estimates (and associated standard errors, t-statistics and p-values), as well as the R2, the adjusted R2, and the relevant F-ratio and associated p-value.
- INSTRUCTIONS: Referencing the regression output, interpret the results as in the example included above this report outline.
- NOTE: YOUR DEPENDENT VARIABLE (AND SOME PREDICTORS) WOULD BE LOG-TRANSFORMED. LOOK AT THE SLIDES FOR EXAMPLES OF INTERPRETING REGRESSION OUTPUT WITH LOG-TRANSFORMED VARIABLES.
Call:
lm(formula = LNMEDHVAL ~ PCTVACANT + PCTSINGLES + PCTBACHMOR +
LNNBELPOV100, data = regress_data)
Residuals:
Min 1Q Median 3Q Max
-2.25825 -0.20391 0.03822 0.21744 2.24347
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 11.1137661 0.0465330 238.836 < 0.0000000000000002 ***
PCTVACANT -0.0191569 0.0009779 -19.590 < 0.0000000000000002 ***
PCTSINGLES 0.0029769 0.0007032 4.234 0.0000242 ***
PCTBACHMOR 0.0209098 0.0005432 38.494 < 0.0000000000000002 ***
LNNBELPOV100 -0.0789054 0.0084569 -9.330 < 0.0000000000000002 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.3665 on 1715 degrees of freedom
Multiple R-squared: 0.6623, Adjusted R-squared: 0.6615
F-statistic: 840.9 on 4 and 1715 DF, p-value: < 0.00000000000000022Residuals Observations: Residuals are differences between observed values and values predicted by regression model.
Min: Value of -2.25825 is smallest residual. Means largest underestimation made by model was by that many units.
Q1 (First Quartile): Value of -0.20391 means 25% of residuals are less than that value, and are points that are underestimations by the model.
Median: Value of 0.04735 means 50% of residuals are less than that value, and other 50% are higher. Median near zero suggests, on whole, model is not systematically overestimating or underestimating.
Q3 (Third Quartile): Value of 0.21744 means 75% of residuals are less than that value, and are points that are underestimations by the model.
Max: Value of 2.24347 is largest residual. Means largest overestimation made by model was by that many units.
Coefficients Observations:
Estimate: Indicates expected change in dependent variable LNMEDHVAL for each one-unit increase in respective independent variable.
Intercept (Constant): Y-intercept of regression line. Represents expected value of dependent variable when all independent variables are zero, so the dependent variable LNMEDHVAL is expected to be around 11.1137661.
- P-Value is less than 0.001, so the null hypothesis that the coefficient of Intercept is zero in the population is rejected.
PCTVACANT: If value of PCTVACANT changes by one unit, value of variable LNMEDHVAL changes by -0.0191569 units.
- P-Value is less than 0.001, so the null hypothesis that the coefficient of PCTVACANT is zero in the population is rejected.
PCTSINGLES: If value of PCTSINGLES changes by one unit, value of variable LNMEDHVAL changes by 0.0029769 units.
- P-Value is less than 0.001, so the null hypothesis that the coefficient of PCTSINGLES is zero in the population is rejected.
PCTBACHMORE: If value of PCTBACHMOR changes by one unit, value of variable LNMEDHVAL changes by 0.0209098 units.
- P-Value is less than 0.001, so the null hypothesis that the coefficient of PCTBACHMORE is zero in the population is rejected.
LNNBELPOV100: If value of PCTBACHMOR changes by one unit, value of variable LNMEDHVAL changes by -0.0789054 units.
- P-Value is less than 0.001, so the null hypothesis that the coefficient of LNNBELPOV100 is zero in the population is rejected.
R Observations:
R (Correlation Coefficient): Correlation coefficient between observed values of dependent variable ln(median house value) and predictions made by model using independent variables. R value of ~0.81 (derived from taking square root of “multiple R-squared” or “adjusted R-squared”) indicates very high positive correlation between observed values and prediction made by model.
R^2 (R-Squared): Proportion of variance in dependent variable that can be explained by independent variables in regression model. R^2 value of 0.6623 means 66.23% of variance in dependent variable is explained by independent variables in model.
Adjusted R^2: Adjusts R^2 value based on number of variables in model and number of observations. More accurate measure when there are multiple independent variables, like in this case. Suggests that after adjusting for number of predictors, value of 0.6615 means about 66.15% of variance in dependent variable is accounted for.
Standard Error of Estimate (Residual Standard Error): Indicates average distance observed values fall from regression line (i.e. measure of accuracy of predictions made with regression model). Value of 0.3665 means that predicted values are, on average, 0.3665 units away from actual variables.
- NOTE: Whether this value is a small or large error depends on the context and scale of the dependent variable.
Degrees of Freedom (df): Indicates number of independent variables in model. There are 4 here, which are PCTVACANT (percent vacant units), PCTSINGLES (percent detached single-family homes), PCTBACHMOR (percent bachelor’s degrees or more), and LNNBELPOV100 (log of number of households in poverty).
F-Statistic (F): Tests overall significance of model. Compares model with no predictors (only intercept, also referred to as constant) with model specified. Value of 819.09 used with degrees of freedom to calculate p-value.
P-Value: All values <0.001, beyond the 0.001 threshold, so results are highly statistically significant. Can reject null hypothesis with high degree of confidence. Very unlikely observed results due to chance, indicating independent variables (predictors) in model have statistically significant effect on dependent variable LNMEDHVAL (log of median house values).
Summary: Model shows very high positive relationship between observed values and prediction, explains 66.15% of variance in dependent variable, but predictions are on average 0.3665 units away from actual values, which may or may not be significant depending on context of data. In this case, the log of median house value is used, and in statistics this means the natural log (i.e. Euler’s constant base e or ln(x)) So that means increasing x (or predictor variable) by 1% is almost equivalent to adding 0.01 to ln(x) according to “Lecture 3-9” slide #144; “For any variable x, small changes in ln(x) may be interpreted as % change in x”.
Regression Assumption Checks
Scatter Plots of Dependent Variable and Predictors
- INSTRUCTIONS: First state that in this section, you will be talking about testing model assumptions. State that you have already looked at the variable distributions earlier.
- INSTRUCTIONS: Present scatter plots of the dependent variable and each of the predictors. State whether each of the relationships seems to be linear, as assumed by the regression model. [Hint: they will not look linear.]
Histogram of Standardized Residuals
- INSTRUCTIONS: Present the histogram of the standardized residuals. State whether the residuals look normal.
Standardized Residual by Predicted Value Scatter Plot
- INSTRUCTIONS: Present the ‘Standardized Residual by Predicted Value’ scatter plot. What conclusions can you draw from that? Does there seem to be heteroscedasticity? Do there seem to be outliers? Anything else? Discuss.
- Mention what standardized residuals are.
- INSTRUCTIONS: Referencing the maps of the dependent variable and the predictors that you presented earlier, state whether there seems to be spatial autocorrelation in your variables. That is, does it seem that the observations (i.e., block groups) are independent of each other? Briefly discuss.
Choropleth Map of Standardized Regression Residuals
- INSTRUCTIONS: Now, present the choropleth map of the standardized regression residuals. Do there seem to be any noticeable spatial patterns in them? That is, do they seem to be spatially autocorrelated?
- You will examine the spatial autocorrelation of the variables and residuals and run spatial regressions in the next assignment.
Additional Models
Stepwise Regression
- INSTRUCTIONS: Present the results of the stepwise regression and state whether all 4 predictors in the original model are kept in the final model.
Start: AIC=-3448.07
LNMEDHVAL ~ PCTVACANT + PCTSINGLES + PCTBACHMOR + LNNBELPOV100
Df Sum of Sq RSS AIC
<none> 230.34 -3448.1
- PCTSINGLES 1 2.407 232.75 -3432.2
- LNNBELPOV100 1 11.692 242.04 -3364.9
- PCTVACANT 1 51.546 281.89 -3102.7
- PCTBACHMOR 1 199.020 429.36 -2379.0 Step Df Deviance Resid. Df Resid. Dev AIC
1 NA NA 1715 230.3435 -3448.073Cross-Validation
- INSTRUCTIONS: Present the cross-validation results – that is, compare the RMSE of the original model that includes all 4 predictors with the RMSE of the model that only includes PCTVACANT and MEDHHINC as predictors.
fold 1
Observations in test set: 344
[,1] [,2] [,3] [,4] [,5] [,6]
Predicted 10.928823 11.005803 10.8946651 11.156140 10.919127 10.627455
cvpred 10.934261 11.011768 10.8997320 11.162871 10.924883 10.631849
LNMEDHVAL 12.672319 12.129192 11.6055046 12.385055 11.998433 13.004930
CV residual 1.738058 1.117424 0.7057727 1.222185 1.073551 2.373081
[,7] [,8] [,9] [,10] [,11] [,12]
Predicted 10.896417 11.051499 11.180060 10.74290 11.1561403 10.8594713
cvpred 10.900359 11.057154 11.186157 10.74793 11.1628706 10.8641690
LNMEDHVAL 11.400876 12.323856 11.918391 11.96527 11.6784399 11.4031106
CV residual 0.500517 1.266702 0.732234 1.21734 0.5155693 0.5389416
[,13] [,14] [,15] [,16] [,17] [,18]
Predicted 10.262233 10.5624839 10.7977414 10.72912686 10.2961868 10.7242481
cvpred 10.260550 10.5635466 10.8029974 10.73410062 10.2993797 10.7254334
LNMEDHVAL 12.323856 10.1345993 10.6310362 10.76002828 11.0020998 11.2424282
CV residual 2.063306 -0.4289474 -0.1719613 0.02592766 0.7027202 0.5169948
[,19] [,20] [,21] [,22] [,23] [,24]
Predicted 10.69176422 10.8787044 10.95832146 10.9710857 10.9051689 10.9108121
cvpred 10.69658428 10.8837142 10.96179629 10.9770548 10.9093259 10.9149336
LNMEDHVAL 10.62132735 11.0728689 10.89302875 10.8742665 10.4659564 10.6286178
CV residual -0.07525694 0.1891547 -0.06876754 -0.1027883 -0.4433695 -0.2863158
[,25] [,26] [,27] [,28] [,29] [,30]
Predicted 10.44421070 10.7378729 10.5568905 11.0070888 11.547155 10.2910026
cvpred 10.44622550 10.7419581 10.5611557 11.0074738 11.543528 10.2933440
LNMEDHVAL 10.54006438 10.3189030 10.4282161 10.0690020 9.268609 9.6927665
CV residual 0.09383888 -0.4230551 -0.1329397 -0.9384718 -2.274918 -0.6005775
[,31] [,32] [,33] [,34] [,35]
Predicted 10.7284836 10.8320902 11.0398745 10.95594470 11.0272967
cvpred 10.7323416 10.8360123 11.0437922 10.96091809 11.0325624
LNMEDHVAL 9.8934372 10.5023241 10.6358554 10.99204951 11.1995836
CV residual -0.8389044 -0.3336882 -0.4079367 0.03113141 0.1670212
[,36] [,37] [,38] [,39] [,40] [,41]
Predicted 11.078192008 10.7973490 10.2680649 10.9019838 10.9603464 10.9314057
cvpred 11.081559988 10.8005450 10.2711420 10.9058642 10.9645022 10.9372116
LNMEDHVAL 11.089805422 11.0697585 9.7699562 10.6016223 10.7254676 10.6942151
CV residual 0.008245434 0.2692135 -0.5011859 -0.3042419 -0.2390346 -0.2429965
[,42] [,43] [,44] [,45] [,46] [,47]
Predicted 10.8666822 10.7497292 10.7960471 11.1688649 10.7088410 10.1293781
cvpred 10.8708257 10.7534367 10.8005133 11.1718346 10.7094443 10.1306073
LNMEDHVAL 10.7298536 10.5105320 10.4912742 10.6188853 10.2715969 10.2435249
CV residual -0.1409721 -0.2429046 -0.3092391 -0.5529493 -0.4378474 0.1129176
[,48] [,49] [,50] [,51] [,52] [,53]
Predicted 11.0589657 10.8687364 11.1747599 10.37805055 10.7110517 10.71292741
cvpred 11.0652962 10.8706253 11.1809970 10.37998466 10.7136652 10.71682628
LNMEDHVAL 10.9331070 10.5891065 10.5078035 10.46595641 10.3254820 10.64304111
CV residual -0.1321893 -0.2815188 -0.6731935 0.08597175 -0.3881832 -0.07378517
[,54] [,55] [,56] [,57] [,58] [,59]
Predicted 10.68046015 10.85651613 10.6569128 10.4079669 10.8465959 10.6100834
cvpred 10.68419961 10.86130405 10.6604576 10.4116195 10.8504153 10.6118023
LNMEDHVAL 10.60410675 10.81777628 10.4659564 10.3022637 10.3513734 11.2910311
CV residual -0.08009286 -0.04352777 -0.1945012 -0.1093558 -0.4990419 0.6792288
[,60] [,61] [,62] [,63] [,64] [,65]
Predicted 10.6739160 10.5432233 10.9291309 10.8309907 10.9819205 11.00942009
cvpred 10.6783856 10.5449840 10.9314804 10.8347690 10.9864208 11.01409530
LNMEDHVAL 11.5655179 11.0300392 10.5505908 10.4912742 10.4042628 11.09589372
CV residual 0.8871323 0.4850552 -0.3808896 -0.3434948 -0.5821579 0.08179842
[,66] [,67] [,68] [,69] [,70]
Predicted 10.96507855 10.64118339 10.56350782 11.2016099 10.7169150
cvpred 10.97037693 10.64579539 10.56732841 11.1992203 10.7218385
LNMEDHVAL 10.95954023 10.67127828 10.54534144 10.4544950 10.6016223
CV residual -0.01083671 0.02548289 -0.02198697 -0.7447253 -0.1202162
[,71] [,72] [,73] [,74] [,75] [,76]
Predicted 10.8966775 10.8781117 10.8414960 10.97821768 10.253328 10.9099322
cvpred 10.8989390 10.8831399 10.8462750 10.97638215 10.255603 10.9126107
LNMEDHVAL 10.4341158 10.5610076 11.1562505 10.91508846 10.491274 10.2921455
CV residual -0.4648232 -0.3221324 0.3099755 -0.06129369 0.235671 -0.6204651
[,77] [,78] [,79] [,80] [,81] [,82]
Predicted 10.6947768 10.5180457 10.6769630 10.687266 10.6512215 10.9582192
cvpred 10.6979037 10.5216408 10.6796131 10.690355 10.6550388 10.9634516
LNMEDHVAL 10.1345993 10.2327913 10.4222813 10.521372 10.8874369 11.1243175
CV residual -0.5633044 -0.2888495 -0.2573317 -0.168983 0.2323981 0.1608659
[,83] [,84] [,85] [,86] [,87] [,88]
Predicted 10.8138039 10.47047072 10.5433231 10.4975070 10.559967 10.655555
cvpred 10.8191260 10.47438048 10.5475326 10.5015280 10.563061 10.655375
LNMEDHVAL 10.7188524 10.43705266 10.2750511 10.1924188 10.081634 10.534759
CV residual -0.1002736 -0.03732782 -0.2724814 -0.3091092 -0.481427 -0.120616
[,89] [,90] [,91] [,92] [,93] [,94]
Predicted 10.6568946 11.1510245 10.5288637 10.6944085 10.5710209 10.8252968
cvpred 10.6550218 11.1559396 10.5330137 10.6992394 10.5708631 10.8298581
LNMEDHVAL 10.4311703 11.0524760 10.4341158 10.5400644 10.2327913 10.3672216
CV residual -0.2238515 -0.1034636 -0.0988979 -0.1591751 -0.3380718 -0.4626366
[,95] [,96] [,97] [,98] [,99] [,100]
Predicted 10.9156544 10.6866884 11.1561403 10.9817558 10.5972353 10.9892113
cvpred 10.9213954 10.6914875 11.1628706 10.9855027 10.6007914 10.9948595
LNMEDHVAL 10.5738777 9.8469172 10.7851868 11.3169106 11.2797316 11.1490820
CV residual -0.3475177 -0.8445703 -0.3776837 0.3314079 0.6789402 0.1542226
[,101] [,102] [,103] [,104] [,105]
Predicted 10.93066097 11.0001661 11.0621508 10.87908249 10.9841928
cvpred 10.93462097 11.0043774 11.0673343 10.88430083 10.9902157
LNMEDHVAL 10.98529272 11.8954631 11.5740206 10.96301245 10.8855660
CV residual 0.05067176 0.8910856 0.5066863 0.07871163 -0.1046497
[,106] [,107] [,108] [,109] [,110] [,111]
Predicted 11.02858643 10.9264762 10.88491035 11.2348813 10.4244959 9.280361
cvpred 11.03426803 10.9313056 10.89052493 11.2335782 10.4282166 9.279375
LNMEDHVAL 10.99373159 11.2212354 10.90595598 11.9524699 11.2567421 10.714418
CV residual -0.04053644 0.2899298 0.01543105 0.7188917 0.8285255 1.435043
[,112] [,113] [,114] [,115] [,116] [,117]
Predicted 11.1561403 11.4279094 10.6410501 10.7654555 10.7852184 11.1792059
cvpred 11.1628706 11.4274408 10.6456615 10.7701332 10.7904229 11.1853252
LNMEDHVAL 11.6307085 11.2252434 11.3997568 10.6188853 11.2252434 11.7605665
CV residual 0.4678379 -0.2021974 0.7540952 -0.1512479 0.4348205 0.5752413
[,118] [,119] [,120] [,121] [,122] [,123]
Predicted 10.457094 11.0083484 10.5513035 10.72467266 10.0686691 10.191371
cvpred 10.460670 11.0129308 10.5530857 10.72840884 10.0697121 10.194133
LNMEDHVAL 11.794338 11.4053403 10.3254820 10.74720759 9.6023825 10.474467
CV residual 1.333668 0.3924094 -0.2276038 0.01879875 -0.4673296 0.280334
[,124] [,125] [,126] [,127] [,128] [,129]
Predicted 11.0718632 10.0018156 10.4792479 10.9891893 10.6214526 10.9797835
cvpred 11.0782469 10.0037975 10.4831938 10.9945899 10.6236737 10.9857884
LNMEDHVAL 10.7144178 10.9595402 10.2750511 11.0284171 9.9330464 10.2219413
CV residual -0.3638291 0.9557427 -0.2081427 0.0338272 -0.6906273 -0.7638471
[,130] [,131] [,132] [,133] [,134] [,135]
Predicted 10.0896566 8.708341 10.9101879 10.6394067 10.7756476 10.694692
cvpred 10.0908995 8.705002 10.9073418 10.6413066 10.7808128 10.698260
LNMEDHVAL 10.3889954 9.769956 10.0774409 10.1105017 10.9886768 10.566176
CV residual 0.2980958 1.064954 -0.8299009 -0.5308049 0.2078641 -0.132085
[,136] [,137] [,138] [,139] [,140] [,141]
Predicted 10.6565005 10.76399708 10.3769041 10.5508328 10.6757600 10.681280
cvpred 10.6603890 10.76848606 10.3759417 10.5497845 10.6790989 10.683255
LNMEDHVAL 10.5159668 10.82774645 10.1185989 9.8201059 11.0508900 10.118599
CV residual -0.1444221 0.05926039 -0.2573428 -0.7296785 0.3717911 -0.564656
[,142] [,143] [,144] [,145] [,146] [,147]
Predicted 10.6855326 10.53494184 10.30280864 10.7313212 10.8476945 10.4443949
cvpred 10.6841224 10.53213658 10.30602871 10.7352090 10.8522512 10.4460346
LNMEDHVAL 10.0475879 10.61888534 10.38899537 10.0982316 10.2576594 9.8984750
CV residual -0.6365345 0.08674876 0.08296665 -0.6369774 -0.5945918 -0.5475595
[,148] [,149] [,150] [,151] [,152] [,153]
Predicted 10.2810335 10.2931966 10.840556 10.3164292 11.176248 10.6625767
cvpred 10.2821382 10.2963771 10.840373 10.3185038 11.181037 10.6665889
LNMEDHVAL 9.5030100 9.3842937 9.803667 9.6091165 10.351373 10.1145585
CV residual -0.7791282 -0.9120834 -1.036706 -0.7093873 -0.829664 -0.5520304
[,154] [,155] [,156] [,157] [,158] [,159]
Predicted 10.7029001 10.4264084 10.624110 10.898743 10.860611 10.4059491
cvpred 10.7065014 10.4280887 10.626983 10.902310 10.862536 10.4044651
LNMEDHVAL 10.0774409 9.9617565 10.021271 9.814656 9.729134 9.7526647
CV residual -0.6290605 -0.4663322 -0.605712 -1.087654 -1.133402 -0.6518005
[,160] [,161] [,162] [,163] [,164] [,165]
Predicted 10.8495833 10.4146901 10.5601878 10.5461431 10.8175932 10.6557530
cvpred 10.8539576 10.4160985 10.5633359 10.5485688 10.8169264 10.6558676
LNMEDHVAL 10.3981838 9.8036672 9.8416121 10.2715969 10.3449631 10.0816337
CV residual -0.4557739 -0.6124312 -0.7217237 -0.2769719 -0.4719633 -0.5742339
[,166] [,167] [,168] [,169] [,170] [,171]
Predicted 10.932473 10.19003804 10.6068749 11.072603 10.9119273 11.156140
cvpred 10.936591 10.19078742 10.6097370 11.078990 10.9173992 11.162871
LNMEDHVAL 10.599132 10.22918769 10.5023241 11.350407 10.7385682 10.829729
CV residual -0.337459 0.03840027 -0.1074129 0.271417 -0.1788309 -0.333142
[,172] [,173] [,174] [,175] [,176]
Predicted 10.9796322 11.1900713 11.0691262 10.814488180 10.55387366
cvpred 10.9839116 11.1959028 11.0739378 10.816939960 10.55610593
LNMEDHVAL 10.9595402 11.0572191 11.0153451 10.815770263 10.46595641
CV residual -0.0243714 -0.1386836 -0.0585927 -0.001169697 -0.09014952
[,177] [,178] [,179] [,180] [,181] [,182]
Predicted 11.0474883 10.5599891 11.1561403 11.0732324 10.8798220 10.7608102
cvpred 11.0517882 10.5622995 11.1628706 11.0790466 10.8843942 10.7651351
LNMEDHVAL 10.5815211 10.4222813 10.7493558 10.8551454 10.7747809 10.3577428
CV residual -0.4702671 -0.1400182 -0.4135148 -0.2239012 -0.1096133 -0.4073922
[,183] [,184] [,185] [,186] [,187] [,188]
Predicted 10.9144354 10.4282644 10.762502 11.2831794 10.7027570 10.7556697
cvpred 10.9201714 10.4280791 10.765373 11.2865446 10.7070955 10.7586306
LNMEDHVAL 10.4631033 10.2611620 10.288750 10.7557730 10.3254820 10.3951304
CV residual -0.4570681 -0.1669171 -0.476623 -0.5307716 -0.3816135 -0.3635003
[,189] [,190] [,191] [,192] [,193] [,194]
Predicted 10.6413739 10.54567851 10.8123297 10.9104442 10.569183 10.2676275
cvpred 10.6459866 10.54989764 10.8112725 10.9143816 10.571455 10.2688229
LNMEDHVAL 10.4716382 10.48010092 10.0212706 10.2819240 10.385914 10.1503476
CV residual -0.1743484 -0.06979673 -0.7900019 -0.6324577 -0.185541 -0.1184753
[,195] [,196] [,197] [,198] [,199] [,200]
Predicted 10.7073859 10.4938164 10.191656729 11.3250973 10.4433242 11.0947947
cvpred 10.7101429 10.4968406 10.193612610 11.3273521 10.4446501 11.1000317
LNMEDHVAL 10.2681307 10.0732303 10.196157166 10.4222813 10.3287553 11.2398035
CV residual -0.4420122 -0.4236102 0.002544556 -0.9050707 -0.1158948 0.1397719
[,201] [,202] [,203] [,204] [,205] [,206]
Predicted 10.9498249 11.1190159 10.8814761 11.0698743 10.9890603 11.2296275
cvpred 10.9544051 11.1250203 10.8845668 11.0745046 10.9933005 11.2309304
LNMEDHVAL 11.2009507 11.3839551 11.0681996 11.3034382 11.3702092 11.3397618
CV residual 0.2465456 0.2589348 0.1836328 0.2289336 0.3769087 0.1088314
[,207] [,208] [,209] [,210] [,211] [,212]
Predicted 11.0659455 10.9670126 11.5114866 11.1853005 11.1918976 11.2562967
cvpred 11.0710766 10.9698166 11.5053346 11.1894689 11.1956788 11.2577930
LNMEDHVAL 11.2502612 11.3108093 11.7613468 11.6018517 11.7566556 11.7134143
CV residual 0.1791845 0.3409927 0.2560122 0.4123828 0.5609769 0.4556214
[,213] [,214] [,215] [,216] [,217] [,218]
Predicted 11.7189053 11.38315 11.726522 11.1413023 11.1324047 11.7686700
cvpred 11.7093025 11.37992 11.712523 11.1433719 11.1368896 11.7591749
LNMEDHVAL 11.9582521 12.32386 13.645671 11.7829526 11.4563551 12.5974388
CV residual 0.2489496 0.94394 1.933147 0.6395807 0.3194655 0.8382639
[,219] [,220] [,221] [,222] [,223] [,224]
Predicted 10.9278718 11.0635527 10.8289590 10.8103120 10.5556929 11.2473772
cvpred 10.9333202 11.0699021 10.8326097 10.8156198 10.5593663 11.2516907
LNMEDHVAL 11.1243175 11.3132543 10.4516090 11.4489201 11.0806029 11.1418618
CV residual 0.1909973 0.2433522 -0.3810008 0.6333004 0.5212366 -0.1098289
[,225] [,226] [,227] [,228] [,229] [,230]
Predicted 10.76418601 10.63999144 10.6279411 10.6981430 10.6801698 11.0169265
cvpred 10.76652823 10.64156222 10.6317084 10.7017202 10.6839649 11.0182815
LNMEDHVAL 10.74720759 10.68281243 10.1811193 10.6572594 10.5427064 11.4845260
CV residual -0.01932064 0.04125021 -0.4505892 -0.0444608 -0.1412586 0.4662445
[,231] [,232] [,233] [,234] [,235] [,236]
Predicted 10.813646 11.1188266 11.3366798 10.9238301 11.06895465 11.2098095
cvpred 10.817589 11.1224882 11.3386278 10.9287212 11.07378736 11.2151181
LNMEDHVAL 12.016122 11.8159886 11.0989240 11.0619398 11.02190247 11.4360444
CV residual 1.198533 0.6935004 -0.2397038 0.1332186 -0.05188489 0.2209263
[,237] [,238] [,239] [,240] [,241]
Predicted 10.95854249 11.1561403 11.13999769 11.0646605 10.88838344
cvpred 10.96372947 11.1628706 11.14356968 11.0710145 10.89323912
LNMEDHVAL 11.04771035 10.8117461 11.10945836 10.9472916 10.96127785
CV residual 0.08398089 -0.3511245 -0.03411132 -0.1237229 0.06803873
[,242] [,243] [,244] [,245] [,246] [,247]
Predicted 11.2438682 11.1734634 10.87422631 10.8609383 11.0423640 11.1528443
cvpred 11.2482747 11.1797348 10.87872472 10.8651123 11.0389936 11.1507331
LNMEDHVAL 10.6642934 10.6572594 10.96127785 11.1927202 11.4616322 11.4917018
CV residual -0.5839813 -0.5224755 0.08255312 0.3276079 0.4226386 0.3409687
[,248] [,249] [,250] [,251] [,252]
Predicted 11.1427612 11.4208020 11.09162660 10.80004733 11.1329874
cvpred 11.1451813 11.4159177 11.09460140 10.80418270 11.1379487
LNMEDHVAL 11.6622072 11.7905572 11.06819964 10.90227951 10.7363967
CV residual 0.5170259 0.3746395 -0.02640176 0.09809681 -0.4015521
[,253] [,254] [,255] [,256] [,257] [,258]
Predicted 11.00972126 11.17001102 10.7186418 11.0234770 10.7284758 10.7872200
cvpred 11.01584925 11.17637390 10.7235725 11.0281267 10.7319498 10.7914226
LNMEDHVAL 11.09285420 11.08521475 10.8855660 10.7934343 10.9259385 10.4602421
CV residual 0.07700495 -0.09115915 0.1619936 -0.2346924 0.1939887 -0.3311805
[,259] [,260] [,261] [,262] [,263] [,264]
Predicted 11.1391030 10.52389580 11.0022937 10.4216929 11.1364688 10.992625
cvpred 11.1424998 10.52802533 11.0068781 10.4227543 11.1393503 10.996950
LNMEDHVAL 10.5713169 10.55841352 10.6805162 10.9384498 10.9132686 10.558414
CV residual -0.5711828 0.03038819 -0.3263619 0.5156955 -0.2260816 -0.438537
[,265] [,266] [,267] [,268] [,269] [,270]
Predicted 10.76605685 10.9433209 10.9129822 11.0900729 11.05559446 11.0546502
cvpred 10.77067137 10.9455693 10.9159483 11.0921831 11.06191115 11.0559396
LNMEDHVAL 10.75363848 10.8097279 10.7166375 10.2146420 11.02026715 10.8551454
CV residual -0.01703289 -0.1358413 -0.1993108 -0.8775411 -0.04164401 -0.2007942
[,271] [,272] [,273] [,274] [,275] [,276]
Predicted 11.1014479 10.9185836 11.014607 11.1717524 10.47786236 10.70290817
cvpred 11.1021543 10.9219457 11.020755 11.1748765 10.47951190 10.70646529
LNMEDHVAL 10.5078035 10.6164374 10.714418 10.4631033 10.41331268 10.69421506
CV residual -0.5943508 -0.3055084 -0.306337 -0.7117732 -0.06619922 -0.01225022
[,277] [,278] [,279] [,280] [,281]
Predicted 10.9167768 10.4815768 11.34821763 11.1209602 10.9424782
cvpred 10.9217739 10.4849847 11.34985997 11.1267299 10.9456923
LNMEDHVAL 10.5479696 10.7684850 11.39639165 11.2424282 10.8137602
CV residual -0.3738044 0.2835003 0.04653168 0.1156983 -0.1319321
[,282] [,283] [,284] [,285] [,286] [,287]
Predicted 10.890059862 11.0737027 11.0592315 11.2096589 10.5076080 11.0765475
cvpred 10.894613413 11.0785264 11.0647794 11.2149716 10.5116705 11.0818585
LNMEDHVAL 10.885566025 10.7789563 10.8723707 11.0603687 10.7810375 10.7621492
CV residual -0.009047388 -0.2995701 -0.1924087 -0.1546028 0.2693669 -0.3197094
[,288] [,289] [,290] [,291] [,292] [,293]
Predicted 11.0318057 10.973321 11.16772191 11.1622223 11.7483945 11.28919376
cvpred 11.0359902 10.978598 11.16805657 11.1653358 11.7328129 11.29239959
LNMEDHVAL 11.1899616 10.858999 11.25156070 11.4804023 11.6307085 11.27593651
CV residual 0.1539714 -0.119599 0.08350413 0.3150665 -0.1021044 -0.01646308
[,294] [,295] [,296] [,297] [,298]
Predicted 10.94165268 10.96370819 10.8379406 11.00675637 11.07677020
cvpred 10.94750068 10.96880593 10.8416404 11.01287217 11.08196244
LNMEDHVAL 11.03327546 10.94552949 11.0635085 11.11095425 11.04132055
CV residual 0.08577478 -0.02327644 0.2218681 0.09808207 -0.04064188
[,299] [,300] [,301] [,302] [,303] [,304]
Predicted 11.06488778 11.078083 10.91977228 11.1993291 11.1484471 10.9266599
cvpred 11.06954436 11.079522 10.92431633 11.2049153 11.1542581 10.9296136
LNMEDHVAL 11.04611673 10.938450 10.92052819 10.8197783 11.0493014 10.6164374
CV residual -0.02342763 -0.141072 -0.00378814 -0.3851371 -0.1049567 -0.3131763
[,305] [,306] [,307] [,308] [,309] [,310]
Predicted 11.0844786 11.1561403 11.1005892 11.1063358 10.696081397 11.0996249
cvpred 11.0892521 11.1628706 11.1021331 11.1098405 10.700919222 11.1026012
LNMEDHVAL 11.0728689 10.6139834 11.3083583 11.2935249 10.696480068 10.9920495
CV residual -0.0163832 -0.5488872 0.2062252 0.1836844 -0.004439154 -0.1105517
[,311] [,312] [,313] [,314] [,315] [,316]
Predicted 11.01455904 10.915711 11.2129270 11.1851965 11.7999620 11.0779653
cvpred 11.02070693 10.920439 11.2181531 11.1911571 11.7871471 11.0825610
LNMEDHVAL 10.95430918 11.083680 11.4175153 11.4230008 11.7027190 11.3678997
CV residual -0.06639776 0.163241 0.1993622 0.2318436 -0.0844281 0.2853387
[,317] [,318] [,319] [,320] [,321] [,322]
Predicted 11.0928488 11.0930339 11.1533610 11.115380 11.0833025 11.31984561
cvpred 11.0979439 11.0970458 11.1560473 11.118904 11.0869321 11.31822226
LNMEDHVAL 11.2885311 11.4240943 11.5898865 11.421906 11.3361883 11.38053628
CV residual 0.1905873 0.3270485 0.4338392 0.303002 0.2492562 0.06231402
[,323] [,324] [,325] [,326] [,327] [,328]
Predicted 11.1309718 11.31590974 11.2266184 11.1310695 11.2202991 11.2962940
cvpred 11.1317986 11.31840789 11.2283934 11.1345341 11.2208376 11.2964025
LNMEDHVAL 11.3930152 11.37251331 11.4425030 11.4521133 11.5991032 11.6733422
CV residual 0.2612166 0.05410542 0.2141096 0.3175792 0.3782655 0.3769397
[,329] [,330] [,331] [,332] [,333] [,334]
Predicted 11.5179686 11.0589070 11.2479960 11.7441109 11.0964921 11.2672832
cvpred 11.5136663 11.0649403 11.2491138 11.7352664 11.1021723 11.2710694
LNMEDHVAL 11.6622072 11.6163842 11.4552964 11.7068462 11.5199011 11.6342578
CV residual 0.1485409 0.5514439 0.2061825 -0.0284202 0.4177288 0.3631883
[,335] [,336] [,337] [,338] [,339] [,340]
Predicted 11.72942725 11.4313657 11.1167180 11.6223507 11.2503490 11.1735889
cvpred 11.72054930 11.4283908 11.1205605 11.6167315 11.2518267 11.1780370
LNMEDHVAL 11.77759476 11.7051974 11.3850921 11.8182018 11.4230008 11.4031106
CV residual 0.05704546 0.2768066 0.2645316 0.2014703 0.1711741 0.2250736
[,341] [,342] [,343] [,344]
Predicted 11.1699645 11.1333300 11.1561403 11.380264
cvpred 11.1763286 11.1396849 11.1628706 11.381057
LNMEDHVAL 11.4008760 11.3690551 11.4616322 11.628929
CV residual 0.2245474 0.2293702 0.2987616 0.247872
Sum of squares = 87.79 Mean square = 0.26 n = 344
fold 2
Observations in test set: 344
[,1] [,2] [,3] [,4] [,5] [,6]
Predicted 11.5471551 10.382632 10.93935124 11.156140 10.881149 11.0501996
cvpred 11.5226798 10.393005 10.95226485 11.170043 10.891786 11.0610399
LNMEDHVAL 12.3238557 13.017003 10.97335737 12.595747 12.655555 11.9563284
CV residual 0.8011758 2.623998 0.02109253 1.425704 1.763769 0.8952885
[,7] [,8] [,9] [,10] [,11] [,12]
Predicted 11.07935 10.9458819 10.5259683 10.7568300 10.6206079 10.836133
cvpred 11.08529 10.9458202 10.5237532 10.7578472 10.6279101 10.844051
LNMEDHVAL 12.46342 10.7995756 10.7144178 10.8874369 11.5843155 11.998433
CV residual 1.37813 -0.1462446 0.1906646 0.1295898 0.9564053 1.154383
[,13] [,14] [,15] [,16] [,17] [,18]
Predicted 10.4420901 11.017509 10.8334363 10.8233071 10.5943889 10.7215496
cvpred 10.4494543 11.025811 10.8433841 10.8235991 10.5860373 10.7334692
LNMEDHVAL 10.7684850 12.138864 11.4446466 10.2989023 10.1385597 10.1464337
CV residual 0.3190307 1.113053 0.6012626 -0.5246968 -0.4474777 -0.5870354
[,19] [,20] [,21] [,22] [,23] [,24]
Predicted 10.3349640 10.35152830 10.6124121 10.8086441 10.5792130 11.0036399
cvpred 10.3417320 10.36090206 10.6159201 10.8147512 10.5805379 11.0006409
LNMEDHVAL 10.0345158 10.27505111 10.0345158 11.2541547 11.2064003 11.0603687
CV residual -0.3072162 -0.08585095 -0.5814043 0.4394035 0.6258624 0.0597279
[,25] [,26] [,27] [,28] [,29] [,30]
Predicted 10.9626852 10.6990321 10.9309994 10.30769198 10.54732591 10.9089041
cvpred 10.9601757 10.7074268 10.9358692 10.31461731 10.55549239 10.9184150
LNMEDHVAL 11.4186148 10.8356516 11.0681996 10.39818379 10.61888534 10.8056794
CV residual 0.4584391 0.1282248 0.1323304 0.08356648 0.06339295 -0.1127357
[,31] [,32] [,33] [,34] [,35] [,36]
Predicted 10.9400223 11.0289264 10.67996848 10.7428085 10.9248093 10.7168680
cvpred 10.9430137 11.0302344 10.68763855 10.7548251 10.9376566 10.7200487
LNMEDHVAL 10.7077288 10.7975327 10.76848499 11.0603687 11.0943751 10.0690020
CV residual -0.2352849 -0.2327017 0.08084644 0.3055436 0.1567185 -0.6510467
[,37] [,38] [,39] [,40] [,41] [,42]
Predicted 10.6779304 10.8108458 10.5956476 10.9451718 10.6898097 10.2735165
cvpred 10.6785324 10.8178826 10.5944834 10.9467034 10.6947440 10.2798281
LNMEDHVAL 10.5687495 10.4829060 10.0858091 10.3545632 9.8416121 9.8469172
CV residual -0.1097828 -0.3349767 -0.5086743 -0.5921403 -0.8531318 -0.4329109
[,43] [,44] [,45] [,46] [,47] [,48]
Predicted 10.9070562 10.2403851 11.1561403 11.0428455 10.8900781 10.9639322
cvpred 10.9179667 10.2412751 11.1700433 11.0503058 10.9000700 10.9711990
LNMEDHVAL 10.2327913 10.5213722 11.6386767 11.2437380 10.6041067 11.1198829
CV residual -0.6851754 0.2800971 0.4686334 0.1934322 -0.2959633 0.1486838
[,49] [,50] [,51] [,52] [,53] [,54]
Predicted 10.5142600 10.6092219 10.5682258 10.8462145 10.8029784 10.91733453
cvpred 10.5134827 10.6105337 10.5774698 10.8587030 10.8079628 10.92677060
LNMEDHVAL 9.9183762 9.9427083 10.7121931 11.0284171 11.0524760 10.87047140
CV residual -0.5951065 -0.6678254 0.1347233 0.1697141 0.2445133 -0.05629921
[,55] [,56] [,57] [,58] [,59] [,60]
Predicted 10.939444 11.1499886 9.623473 11.22372308 11.156140 10.69219213
cvpred 10.949098 11.1538526 9.628001 11.23099281 11.170043 10.69909218
LNMEDHVAL 11.144756 11.3527567 11.824812 11.31080928 11.303438 10.65960953
CV residual 0.195658 0.1989041 2.196811 0.07981647 0.133395 -0.03948265
[,61] [,62] [,63] [,64] [,65] [,66]
Predicted 11.08816347 10.7986194 10.572374078 10.851903 10.8093565 11.0221198
cvpred 11.09594367 10.8003808 10.567438969 10.856609 10.8216769 11.0294160
LNMEDHVAL 11.01862914 10.3889954 10.561007555 10.566176 10.5840560 10.1266311
CV residual -0.07731453 -0.4113854 -0.006431414 -0.290433 -0.2376209 -0.9027849
[,67] [,68] [,69] [,70] [,71] [,72]
Predicted 10.7917895 10.872702 10.8729262 10.3196288 11.0762739 10.7049671
cvpred 10.7981317 10.877373 10.8747495 10.3221343 11.0870561 10.7097235
LNMEDHVAL 10.6237634 10.410305 10.4516090 10.5050675 10.2819240 10.9818971
CV residual -0.1743683 -0.467068 -0.4231406 0.1829332 -0.8051321 0.2721736
[,73] [,74] [,75] [,76] [,77] [,78]
Predicted 10.6979284 10.702019 10.9650490 10.79161485 11.0029095 10.7321127
cvpred 10.7085515 10.709183 10.9759207 10.80385420 11.0083037 10.7411585
LNMEDHVAL 11.4710613 11.717498 10.6572594 10.78725509 10.6896696 10.5347593
CV residual 0.7625098 1.008315 -0.3186613 -0.01659911 -0.3186341 -0.2063992
[,79] [,80] [,81] [,82] [,83] [,84]
Predicted 10.9245489 10.6113210 10.7891579 10.84586210 10.9331707 11.0673645
cvpred 10.9312498 10.6180519 10.8013860 10.85834903 10.9460561 11.0775428
LNMEDHVAL 10.5713169 10.7705880 11.0332755 10.87804719 11.7675677 11.9336075
CV residual -0.3599328 0.1525361 0.2318895 0.01969816 0.8215116 0.8560647
[,85] [,86] [,87] [,88] [,89] [,90]
Predicted 11.0992710 10.3399733 10.922366 10.5429111 10.9715313 10.5521770
cvpred 11.1129144 10.3483139 10.932794 10.5508464 10.9675833 10.5591892
LNMEDHVAL 11.9595325 10.6712783 10.218298 10.3155972 10.6115233 10.6759079
CV residual 0.8466181 0.3229644 -0.714496 -0.2352492 -0.3560599 0.1167187
[,91] [,92] [,93] [,94] [,95]
Predicted 11.1561403 10.9875450 10.59233608 10.631374506 10.59568307
cvpred 11.1700433 10.9993072 10.60013409 10.642882544 10.59736704
LNMEDHVAL 11.4467857 11.2279065 10.61643736 10.635855446 10.50780352
CV residual 0.2767424 0.2285993 0.01630327 -0.007027098 -0.08956352
[,96] [,97] [,98] [,99] [,100] [,101]
Predicted 10.5161918 10.0785915 10.9251682 10.0814267 10.4024629 9.6693992
cvpred 10.5225803 10.0875767 10.9329443 10.0885992 10.4093448 9.6765169
LNMEDHVAL 10.4429006 10.4222813 10.2819240 10.1924188 10.0562086 10.6406516
CV residual -0.0796797 0.3347046 -0.6510203 0.1038197 -0.3531361 0.9641348
[,102] [,103] [,104] [,105] [,106] [,107]
Predicted 10.4792479 10.6811145 10.4924760 10.6303101 10.21595096 10.188752
cvpred 10.4900617 10.6731698 10.4969910 10.6298798 10.21838885 10.191418
LNMEDHVAL 10.1425045 9.8521943 9.9987977 10.1023384 10.23995979 9.873028
CV residual -0.3475572 -0.8209755 -0.4981933 -0.5275414 0.02157094 -0.318390
[,108] [,109] [,110] [,111] [,112] [,113]
Predicted 10.519585 10.4134522 10.148396 9.9704933 10.8232794 10.6664262
cvpred 10.530583 10.4239657 10.157700 9.9784972 10.8306896 10.6780942
LNMEDHVAL 9.595603 9.6091165 10.471638 10.1773242 10.3951304 10.5713169
CV residual -0.934980 -0.8148492 0.313938 0.1988271 -0.4355592 -0.1067773
[,114] [,115] [,116] [,117] [,118] [,119]
Predicted 10.9114507 11.5492745 11.2067470 11.6053067 11.0580697 11.110642
cvpred 10.9188819 11.5245912 11.2011917 11.5751239 11.0691375 11.116569
LNMEDHVAL 10.7276630 11.9848023 11.3952674 12.0411980 11.3290026 11.486581
CV residual -0.1912189 0.4602111 0.1940757 0.4660741 0.2598651 0.370012
[,120] [,121] [,122] [,123] [,124] [,125]
Predicted 10.336883 10.8983015 11.0713672 11.2454630 9.2167684 11.15614028
cvpred 10.347047 10.9085287 11.0671538 11.2505989 9.2218203 11.17004328
LNMEDHVAL 11.630709 11.4584693 11.3952674 11.4108927 9.8416121 11.21586623
CV residual 1.283662 0.5499406 0.3281136 0.1602938 0.6197918 0.04582295
[,126] [,127] [,128] [,129] [,130] [,131]
Predicted 10.3490913 11.07368851 10.911260 10.6225571 10.9913796 11.0864963
cvpred 10.3593111 11.08721521 10.923036 10.6287078 11.0045306 11.0924140
LNMEDHVAL 11.0821425 11.06350847 11.986049 10.7557730 11.3337988 11.5356650
CV residual 0.7228315 -0.02370674 1.063014 0.1270651 0.3292681 0.4432509
[,132] [,133] [,134] [,135] [,136] [,137]
Predicted 11.0154479 10.5323175 10.5091791 10.6858113 9.9435823 9.8374028
cvpred 11.0287088 10.5433734 10.5154089 10.6888622 9.9336549 9.8367679
LNMEDHVAL 11.3736634 11.0120502 10.2219413 9.8781697 10.2921455 9.2965181
CV residual 0.3449546 0.4686767 -0.2934676 -0.8106924 0.3584906 -0.5402498
[,138] [,139] [,140] [,141] [,142] [,143]
Predicted 9.5499110 10.3672895 10.4398664 9.737716 10.674360 10.8536065
cvpred 9.5533067 10.3680474 10.4505004 9.735698 10.682630 10.8550727
LNMEDHVAL 9.7699562 10.9150885 11.3144745 11.042922 11.461632 11.0635085
CV residual 0.2166494 0.5470411 0.8639741 1.307223 0.779002 0.2084358
[,144] [,145] [,146] [,147] [,148] [,149]
Predicted 10.753701 10.1265783 10.7647753 10.2200997 10.2129226 10.3474368
cvpred 10.764658 10.1204730 10.7768922 10.2297308 10.2161181 10.3519294
LNMEDHVAL 9.384294 9.5178251 10.5713169 11.1830315 9.3413686 10.0301202
CV residual -1.380364 -0.6026479 -0.2055753 0.9533008 -0.8747495 -0.3218092
[,150] [,151] [,152] [,153] [,154] [,155]
Predicted 10.8390907 10.9601672 9.8174097 10.570291 10.1490445 9.93095535
cvpred 10.8447606 10.9703011 9.8229716 10.578156 10.1470710 9.93505492
LNMEDHVAL 9.9134379 10.1064284 9.5324239 9.735069 9.2103404 9.94750444
CV residual -0.9313227 -0.8638727 -0.2905477 -0.843087 -0.9367306 0.01244951
[,156] [,157] [,158] [,159] [,160] [,161]
Predicted 10.1550705 11.2363484 11.29249 11.1561403 10.75084429 10.920166
cvpred 10.1537286 11.2423790 11.28223 11.1700433 10.74782192 10.920060
LNMEDHVAL 10.6041067 10.4163112 10.03012 10.7144178 10.77687078 9.888374
CV residual 0.4503782 -0.8260678 -1.25211 -0.4556255 0.02904886 -1.031686
[,162] [,163] [,164] [,165] [,166] [,167]
Predicted 10.5505649 10.560941 10.6601409 10.0885392 10.766920 10.3271527
cvpred 10.5582074 10.572128 10.6717802 10.0866106 10.771190 10.3340991
LNMEDHVAL 10.2291877 9.553930 10.2681307 10.2646524 9.740969 9.8626656
CV residual -0.3290197 -1.018198 -0.4036495 0.1780418 -1.030222 -0.4714336
[,168] [,169] [,170] [,171] [,172] [,173]
Predicted 10.898071 10.5800281 10.7455632 10.7843885 10.7109861 10.7361904
cvpred 10.908744 10.5792045 10.7516681 10.7939504 10.7144265 10.7356585
LNMEDHVAL 10.515967 10.2715969 10.5078035 9.9522777 9.8574436 9.9758082
CV residual -0.392777 -0.3076076 -0.2438645 -0.8416727 -0.8569829 -0.7598503
[,174] [,175] [,176] [,177] [,178] [,179]
Predicted 10.5274924 10.8297111 10.4637640 10.670912 10.4711496 10.5962877
cvpred 10.5296616 10.8232173 10.4719667 10.670410 10.4805247 10.5974686
LNMEDHVAL 9.6803440 9.9475044 9.6677652 9.947504 9.6803440 9.7350689
CV residual -0.8493176 -0.8757129 -0.8042015 -0.722906 -0.8001807 -0.8623996
[,180] [,181] [,182] [,183] [,184] [,185]
Predicted 10.6356246 10.3751940 10.84573957 11.2307210 11.1194918 11.0056331
cvpred 10.6322813 10.3797147 10.84587613 11.2373038 11.1201850 11.0074900
LNMEDHVAL 10.1064284 9.8984750 10.79957558 10.6666271 10.9022795 10.9472916
CV residual -0.5258529 -0.4812397 -0.04630055 -0.5706767 -0.2179055 -0.0601984
[,186] [,187] [,188] [,189] [,190] [,191]
Predicted 10.43889721 10.7130911 11.1046161 10.9137307 11.1616645 10.4719294
cvpred 10.44763839 10.7195334 11.1149957 10.9265274 11.1712339 10.4754310
LNMEDHVAL 10.46310334 10.4716382 10.8570741 10.7913788 10.9277354 10.0941079
CV residual 0.01546495 -0.2478951 -0.2579216 -0.1351486 -0.2434985 -0.3813231
[,192] [,193] [,194] [,195] [,196] [,197]
Predicted 10.8679018 10.6406454 10.8092102 10.7419758 10.5897029 11.1561403
cvpred 10.8716979 10.6453178 10.8073729 10.7486143 10.5937613 11.1700433
LNMEDHVAL 10.5505908 10.3320179 10.3734912 9.8626656 9.8883739 10.2363820
CV residual -0.3211071 -0.3132999 -0.4338817 -0.8859488 -0.7053874 -0.9336613
[,198] [,199] [,200] [,201] [,202] [,203]
Predicted 10.7703331 11.044837 10.8371137 10.7866761 10.981804 10.961763
cvpred 10.7746448 11.047465 10.8479588 10.7897584 10.984871 10.953188
LNMEDHVAL 10.3155972 9.975808 9.9281802 10.1542463 9.546813 9.878170
CV residual -0.4590476 -1.071657 -0.9197786 -0.6355121 -1.438058 -1.075018
[,204] [,205] [,206] [,207] [,208]
Predicted 10.4742334 10.6073339 10.415958844 10.7345322 10.8261799
cvpred 10.4810867 10.6098913 10.419355643 10.7395247 10.8380192
LNMEDHVAL 9.9034876 10.3609124 10.410305155 10.3320179 10.3320179
CV residual -0.5775991 -0.2489789 -0.009050489 -0.4075067 -0.5060013
[,209] [,210] [,211] [,212] [,213] [,214]
Predicted 11.25126841 11.1631816 11.1190132 12.0228906 11.3497081 11.860942
cvpred 11.25583455 11.1649929 11.1195339 11.9517218 11.3252206 11.797844
LNMEDHVAL 11.31203252 11.2822536 11.3782506 11.7737501 11.8726956 12.881819
CV residual 0.05619797 0.1172607 0.2587166 -0.1779717 0.5474751 1.083976
[,215] [,216] [,217] [,218] [,219] [,220]
Predicted 11.91837 11.228825 12.0685091 11.3030495 11.13536094 10.9873967
cvpred 11.85746 11.222009 11.9928627 11.2930232 11.12585512 10.9829896
LNMEDHVAL 13.06346 12.351471 12.8762071 11.9754008 11.22524339 11.2721270
CV residual 1.20600 1.129462 0.8833443 0.6823776 0.09938827 0.2891374
[,221] [,222] [,223] [,224] [,225] [,226]
Predicted 11.0816618 11.0599787 10.6300118 10.8405193 10.7758788 10.505341
cvpred 11.0829587 11.0611238 10.6384354 10.8372582 10.7821131 10.514295
LNMEDHVAL 11.8371805 11.2593227 11.3896272 11.3034382 11.2683029 10.709963
CV residual 0.7542218 0.1981989 0.7511918 0.4661801 0.4861897 0.195668
[,227] [,228] [,229] [,230] [,231]
Predicted 10.73761577 10.7858439 10.74067592 10.8642722 10.97456826
cvpred 10.73757000 10.7852778 10.74068291 10.8611385 10.98543386
LNMEDHVAL 10.83368119 10.5966347 10.82774645 10.6549036 11.06507464
CV residual 0.09611119 -0.1886431 0.08706354 -0.2062349 0.07964078
[,232] [,233] [,234] [,235] [,236] [,237]
Predicted 11.1057326 10.8242672 11.1121764 11.0926099 11.0589803 11.0403830
cvpred 11.1099289 10.8301529 11.1220341 11.1027874 11.0545516 11.0456535
LNMEDHVAL 11.4865815 10.9612778 11.1746516 11.0681996 10.8395809 11.3278000
CV residual 0.3766526 0.1311249 0.0526175 -0.0345878 -0.2149707 0.2821465
[,238] [,239] [,240] [,241] [,242]
Predicted 11.0477801 11.21363569 11.3325835 11.3261961 11.17475990
cvpred 11.0566993 11.21374411 11.3144038 11.3147516 11.18683538
LNMEDHVAL 11.1968439 11.23321156 11.4855543 11.5655179 11.13604781
CV residual 0.1401446 0.01946746 0.1711505 0.2507663 -0.05078756
[,243] [,244] [,245] [,246] [,247] [,248]
Predicted 11.88017571 10.9511412 11.20491460 11.1228955 10.7090425 11.2374652
cvpred 11.81551867 10.9601754 11.21403038 11.1279292 10.7209050 11.2433861
LNMEDHVAL 11.75508702 11.0759697 11.13895902 11.4731446 11.0219025 11.0120502
CV residual -0.06043165 0.1157943 -0.07507136 0.3452154 0.3009975 -0.2313359
[,249] [,250] [,251] [,252] [,253] [,254]
Predicted 11.0049787 10.92544421 11.0252244 10.8305615 10.976296 10.7749120
cvpred 11.0181918 10.93829435 11.0311014 10.8429786 10.980999 10.7826374
LNMEDHVAL 10.8077057 11.01205017 10.8512770 10.9419959 11.131665 11.0852147
CV residual -0.2104861 0.07375583 -0.1798245 0.0990173 0.150666 0.3025774
[,255] [,256] [,257] [,258] [,259] [,260]
Predicted 11.83358779 11.5438905 11.0510229 11.0243552 11.2591495 10.9901396
cvpred 11.78099907 11.5011039 11.0609030 11.0346267 11.2629421 11.0000837
LNMEDHVAL 11.84150953 11.8026055 11.2528586 11.2305626 10.8742665 10.8628378
CV residual 0.06051045 0.3015016 0.1919556 0.1959359 -0.3886756 -0.1372459
[,261] [,262] [,263] [,264] [,265]
Predicted 10.978941337 10.88687701 10.8919985 10.9911229 10.9400507
cvpred 10.983574254 10.89778960 10.8963005 10.9971009 10.9432346
LNMEDHVAL 10.980195006 10.91326863 11.0429218 10.7995756 10.6358554
CV residual -0.003379248 0.01547903 0.1466214 -0.1975253 -0.3073792
[,266] [,267] [,268] [,269] [,270] [,271]
Predicted 10.8560170 10.8310872 10.6500184 10.94247802 11.1561403 11.0612413
cvpred 10.8685503 10.8349873 10.6581996 10.95540590 11.1700433 11.0626658
LNMEDHVAL 10.5240640 10.8551454 10.9295291 11.03165864 10.6896696 10.6619542
CV residual -0.3444862 0.0201581 0.2713296 0.07625275 -0.4803737 -0.4007116
[,272] [,273] [,274] [,275] [,276] [,277]
Predicted 11.0087371 11.0440850 10.9264639 11.2019877 10.87561254 11.3421568
cvpred 11.0197182 11.0478328 10.9217984 11.2113908 10.88823525 11.3378022
LNMEDHVAL 10.5941316 10.9577996 10.6358554 10.9114455 10.80364890 10.9560559
CV residual -0.4255866 -0.0900332 -0.2859429 -0.2999453 -0.08458635 -0.3817463
[,278] [,279] [,280] [,281] [,282] [,283]
Predicted 10.8439185 11.0438636 10.50600 10.8466739 10.8958949 11.0760223
cvpred 10.8472407 11.0444087 10.50943 10.8551646 10.8968372 11.0784339
LNMEDHVAL 10.6286178 10.7210623 10.66663 10.5764320 10.7320394 10.8336812
CV residual -0.2186229 -0.3233464 0.15720 -0.2787325 -0.1647978 -0.2447527
[,284] [,285] [,286] [,287] [,288] [,289]
Predicted 10.8868504 10.7909635 10.82760156 10.7049140 11.077725 10.8708128
cvpred 10.8883681 10.7971408 10.83673137 10.7043263 11.074870 10.8799428
LNMEDHVAL 10.7557730 10.6919449 10.92593848 10.5132531 11.225243 10.3417425
CV residual -0.1325951 -0.1051959 0.08920711 -0.1910732 0.150373 -0.5382003
[,290] [,291] [,292] [,293] [,294] [,295]
Predicted 11.1395938 10.758139 11.1288913 11.0800542 10.1193904 11.07328753
cvpred 11.1339484 10.763831 11.1426699 11.0915447 10.1126019 11.06893650
LNMEDHVAL 10.4912742 10.410305 10.9437643 10.5584135 10.4544950 10.98867682
CV residual -0.6426742 -0.353526 -0.1989056 -0.5331311 0.3418931 -0.08025968
[,296] [,297] [,298] [,299] [,300] [,301]
Predicted 10.6564921 10.7703447 11.1767817 11.0483180 10.9833833 11.10411683
cvpred 10.6662023 10.7724012 11.1886587 11.0591039 10.9964979 11.10779416
LNMEDHVAL 10.7975327 10.9818971 11.0300392 11.3265959 11.0974100 11.04611673
CV residual 0.1313304 0.2094959 -0.1586195 0.2674919 0.1009122 -0.06167743
[,302] [,303] [,304] [,305] [,306] [,307]
Predicted 11.0706550 11.0438478 11.29466016 11.179051 11.0316042 11.0181769
cvpred 11.0709446 11.0420371 11.28323883 11.174982 11.0431121 11.0233120
LNMEDHVAL 11.2554492 11.3736634 11.37136190 11.401994 11.1647854 11.3144745
CV residual 0.1845047 0.3316263 0.08812307 0.227012 0.1216733 0.2911626
[,308] [,309] [,310] [,311] [,312]
Predicted 11.06300381 11.07062391 11.04776375 10.9909987 11.18898556
cvpred 11.07191042 11.08029419 11.06006088 11.0041480 11.19966478
LNMEDHVAL 11.08827754 11.03488966 11.03327546 11.1871953 11.21855440
CV residual 0.01636712 -0.04540453 -0.02678542 0.1830473 0.01888963
[,313] [,314] [,315] [,316] [,317] [,318]
Predicted 10.98130406 11.09222699 10.80577 11.0062288 11.0382437 10.73605180
cvpred 10.99440913 11.10583829 10.81562 11.0094293 11.0495763 10.73834312
LNMEDHVAL 11.08980542 11.05564061 11.06194 10.9869862 10.9419959 10.75577295
CV residual 0.09539629 -0.05019769 0.24632 -0.0224431 -0.1075804 0.01742983
[,319] [,320] [,321] [,322] [,323] [,324]
Predicted 10.9584406 11.2574501 10.8981508 11.05929580 11.03362129 10.9730696
cvpred 10.9652314 11.2538770 10.9108763 11.07275681 11.04696512 10.9842956
LNMEDHVAL 11.1690257 11.1375045 11.0136990 11.03488966 10.96992094 11.1562505
CV residual 0.2037943 -0.1163725 0.1028227 -0.03786715 -0.07704418 0.1719549
[,325] [,326] [,327] [,328] [,329] [,330]
Predicted 11.0797404 11.0978848 11.1074580 11.1274658 11.402369745 11.1254913
cvpred 11.0843104 11.1057102 11.1159144 11.1326832 11.384661057 11.1290942
LNMEDHVAL 11.3265959 11.4721035 11.3586081 11.3850921 11.386227812 11.5415129
CV residual 0.2422855 0.3663933 0.2426937 0.2524088 0.001566755 0.4124187
[,331] [,332] [,333] [,334] [,335] [,336]
Predicted 11.1738557 11.3858084 11.1519414 11.0641178 11.082093 11.08590546
cvpred 11.1860200 11.3499982 11.1559780 11.0746239 11.092890 11.09166989
LNMEDHVAL 11.3504065 11.7280368 11.3975146 11.3884954 9.588777 11.10194518
CV residual 0.1643866 0.3780387 0.2415367 0.3138715 -1.504113 0.01027529
[,337] [,338] [,339] [,340] [,341] [,342]
Predicted 11.4185786 12.06850907 11.2745730 11.0832138 11.0914183 11.1473095
cvpred 11.3938371 11.99286275 11.2768518 11.0945193 11.0976828 11.1595119
LNMEDHVAL 11.7996070 11.90968613 11.5926604 11.3621026 11.2984939 11.4053403
CV residual 0.4057699 -0.08317661 0.3158086 0.2675833 0.2008111 0.2458284
[,343] [,344]
Predicted 11.3421069 11.7462686
cvpred 11.3211652 11.7022503
LNMEDHVAL 11.7890409 11.9150517
CV residual 0.4678757 0.2128014
Sum of squares = 99.66 Mean square = 0.29 n = 344
fold 3
Observations in test set: 344
[,1] [,2] [,3] [,4] [,5] [,6]
Predicted 11.1561403 11.1561403 10.623692 10.9841198 11.208922 10.801504
cvpred 11.1407812 11.1407812 10.625120 10.9741842 11.194381 10.798276
LNMEDHVAL 12.1112124 10.9150885 12.323856 11.7027190 12.703509 12.588610
CV residual 0.9704311 -0.2256928 1.698735 0.7285349 1.509128 1.790334
[,7] [,8] [,9] [,10] [,11] [,12]
Predicted 11.037250 10.991327 10.97232 11.129258 11.050267 10.7917700
cvpred 11.025639 10.983769 10.96276 11.116981 11.039215 10.7899285
LNMEDHVAL 12.206073 11.881727 12.34235 12.431214 13.130728 10.6139834
CV residual 1.180434 0.897958 1.37959 1.314233 2.091514 -0.1759451
[,13] [,14] [,15] [,16] [,17] [,18]
Predicted 10.5132235 10.776287 11.043580 11.0089814 10.6082847 10.7654451
cvpred 10.5181344 10.774863 11.032330 11.0030838 10.6145231 10.7624040
LNMEDHVAL 11.3986363 11.326596 12.225385 11.7629057 10.2611620 10.0816337
CV residual 0.8805019 0.551733 1.193055 0.7598219 -0.3533611 -0.6807702
[,19] [,20] [,21] [,22] [,23] [,24]
Predicted 10.5032294 10.5423277 11.04013899 11.2498770 11.0442451 10.8969789
cvpred 10.5106208 10.5485561 11.03063792 11.2359716 11.0348471 10.8908173
LNMEDHVAL 9.9942419 10.4072886 11.00209984 11.4097847 10.8836916 11.1243175
CV residual -0.5163789 -0.1412675 -0.02853808 0.1738131 -0.1511555 0.2335002
[,25] [,26] [,27] [,28] [,29] [,30]
Predicted 10.2325628 10.35922240 10.1755661 10.7084502 10.9974205 10.242298
cvpred 10.2518913 10.37338468 10.1911228 10.7115139 10.9870656 10.255751
LNMEDHVAL 10.1145585 10.32875529 9.8146563 10.5320962 10.1542463 9.510445
CV residual -0.1373328 -0.04462939 -0.3764664 -0.1794177 -0.8328193 -0.745306
[,31] [,32] [,33] [,34] [,35] [,36]
Predicted 11.1023374 11.0313998 11.0409988 11.116702 11.156140 10.8889959
cvpred 11.0886747 11.0214310 11.0317306 11.105094 11.140781 10.8861119
LNMEDHVAL 10.8911683 10.6139834 10.9259385 11.370209 11.831379 10.9954109
CV residual -0.1975064 -0.4074476 -0.1057921 0.265115 0.690598 0.1092989
[,37] [,38] [,39] [,40] [,41] [,42]
Predicted 11.0222371 11.0521756 11.08276117 11.012059 11.0723203 11.21101926
cvpred 11.0131946 11.0400944 11.07043485 11.005285 11.0602924 11.19651121
LNMEDHVAL 11.1447561 10.9004362 11.00542763 11.603680 11.2279065 11.12873249
CV residual 0.1315615 -0.1396582 -0.06500722 0.598395 0.1676141 -0.06777872
[,43] [,44] [,45] [,46] [,47] [,48]
Predicted 11.07294110 10.8766102 11.068804 11.1017815 10.64597038 10.8999050
cvpred 11.06231706 10.8719676 11.056764 11.0910958 10.64669603 10.8937218
LNMEDHVAL 10.98867682 10.7621492 11.473145 10.8257604 10.55059079 10.7121931
CV residual -0.07364024 -0.1098185 0.416381 -0.2653354 -0.09610523 -0.1815287
[,49] [,50] [,51] [,52] [,53] [,54]
Predicted 10.8086060 10.8101565 10.6843367 10.6033360 10.6166485 10.56702129
cvpred 10.8069474 10.8057057 10.6874042 10.6059937 10.6182986 10.57532930
LNMEDHVAL 10.5584135 10.3920676 10.5159668 10.3056138 10.4573727 10.49404814
CV residual -0.2485339 -0.4136381 -0.1714373 -0.3003799 -0.1609259 -0.08128116
[,55] [,56] [,57] [,58] [,59] [,60]
Predicted 11.0662260 10.35967 10.80430209 10.6244915 11.1882474 10.7785915
cvpred 11.0599242 10.37056 10.80440917 10.6286665 11.1733863 10.7762056
LNMEDHVAL 10.5789798 10.60162 10.72985358 10.2146420 11.7852401 11.6154821
CV residual -0.4809444 0.23106 -0.07455559 -0.4140245 0.6118538 0.8392765
[,61] [,62] [,63] [,64] [,65] [,66]
Predicted 10.8902165 10.9458958 11.24737716 10.2429586 10.5732565 10.75707324
cvpred 10.8855117 10.9380657 11.23343291 10.2563904 10.5786587 10.75592463
LNMEDHVAL 11.3468709 10.5023241 11.17184262 10.6596095 10.5105320 10.68738910
CV residual 0.4613592 -0.4357416 -0.06159029 0.4032191 -0.0681267 -0.06853553
[,67] [,68] [,69] [,70] [,71] [,72]
Predicted 10.6165632 10.755043 10.632839 10.6778064 10.892275 9.895062
cvpred 10.6204865 10.752329 10.637361 10.6775283 10.885235 9.920317
LNMEDHVAL 10.2182983 10.545341 10.081634 10.5427064 11.580584 11.044521
CV residual -0.4021882 -0.206988 -0.555727 -0.1348219 0.695349 1.124204
[,73] [,74] [,75] [,76] [,77] [,78]
Predicted 10.8848246 10.65981710 10.9561787 10.6259974 10.5245358 10.6030658
cvpred 10.8780197 10.66010618 10.9471241 10.6283464 10.5302739 10.6083427
LNMEDHVAL 11.7440372 10.56617553 11.2384886 10.8454460 10.7254676 10.3449631
CV residual 0.8660175 -0.09393066 0.2913645 0.2170996 0.1951937 -0.2633796
[,79] [,80] [,81] [,82] [,83] [,84]
Predicted 10.6977884 10.6601047 10.5535731 10.9941950 11.0375663 11.9576035
cvpred 10.6976634 10.6659660 10.5603907 10.9846387 11.0280913 11.9581996
LNMEDHVAL 10.4602421 10.2435249 10.3640720 11.1788504 11.1476421 12.1756134
CV residual -0.2374213 -0.4224411 -0.1963187 0.1942116 0.1195509 0.2174138
[,85] [,86] [,87] [,88] [,89] [,90]
Predicted 10.981228 10.9781360 10.65278261 10.9900974 10.6459704 10.9956055
cvpred 10.977320 10.9683891 10.65545979 10.9850766 10.6466960 10.9878988
LNMEDHVAL 10.789319 11.1718426 10.72546760 10.2072890 10.9022795 10.2146420
CV residual -0.188001 0.2034535 0.07000782 -0.7777876 0.2555835 -0.7732568
[,91] [,92] [,93] [,94] [,95] [,96]
Predicted 10.9471364 10.6801851 10.9166338 10.8299537 10.9735129 11.1702157
cvpred 10.9420451 10.6884704 10.9114961 10.8310668 10.9658996 11.1602647
LNMEDHVAL 10.3889954 10.3920676 11.0235351 10.2109723 10.5213722 10.5294260
CV residual -0.5530497 -0.2964028 0.1120391 -0.6200946 -0.4445274 -0.6308387
[,97] [,98] [,99] [,100] [,101]
Predicted 10.7478461 10.38308575 10.98052676 11.03279901 10.6710119
cvpred 10.7484619 10.39333457 10.97659454 11.02276980 10.6731692
LNMEDHVAL 10.5789798 10.36091240 11.01862914 11.10043574 10.0604913
CV residual -0.1694821 -0.03242217 0.04203461 0.07766595 -0.6126779
[,102] [,103] [,104] [,105] [,106] [,107]
Predicted 11.5388293 11.156140 10.8505968 11.0635177 9.8792871 11.3449066
cvpred 11.5432579 11.140781 10.8459835 11.0510789 9.9041848 11.3324748
LNMEDHVAL 12.1281111 13.345507 11.1272630 11.6307085 10.2989023 10.9295291
CV residual 0.5848532 2.204726 0.2812795 0.5796296 0.3947175 -0.4029456
[,108] [,109] [,110] [,111] [,112] [,113]
Predicted 10.4456787 10.822645 11.1561403 10.3521451 11.0640180 10.164938389
cvpred 10.4527192 10.817800 11.1407812 10.3621345 11.0587156 10.183073283
LNMEDHVAL 11.2897819 12.210563 11.4845260 10.0774409 10.2072890 10.173514690
CV residual 0.8370628 1.392763 0.3437448 -0.2846937 -0.8514266 -0.009558593
[,114] [,115] [,116] [,117] [,118] [,119]
Predicted 10.1597498 10.17757257 10.424127 10.5695622 9.7058735 11.1792798
cvpred 10.1859483 10.19517640 10.440180 10.5758116 9.7416969 11.1642795
LNMEDHVAL 9.8832848 10.14250445 9.752665 9.7925560 9.9617565 11.2708539
CV residual -0.3026634 -0.05267195 -0.687515 -0.7832556 0.2200596 0.1065744
[,120] [,121] [,122] [,123] [,124] [,125]
Predicted 10.6285271 11.0537406 10.8981511 10.3783085 10.7825279 9.6204713
cvpred 10.6413563 11.0416100 10.8921143 10.3874730 10.7830249 9.6703092
LNMEDHVAL 11.2476570 10.3889954 10.6919449 10.9835964 10.3254820 10.3889954
CV residual 0.6063007 -0.6526147 -0.2001694 0.5961234 -0.4575429 0.7186862
[,126] [,127] [,128] [,129] [,130] [,131]
Predicted 10.2159321 10.2139666 10.5850404 10.9437132 10.608837 10.1904223
cvpred 10.2345916 10.2315044 10.5940048 10.9423971 10.612067 10.2077958
LNMEDHVAL 10.5635949 10.5815211 9.7350689 10.0078476 9.417355 10.6572594
CV residual 0.3290033 0.3500167 -0.8589359 -0.9345495 -1.194713 0.4494635
[,132] [,133] [,134] [,135] [,136] [,137]
Predicted 11.1561403 10.0752181 10.5629156 10.7377758 10.7300855 10.7670619
cvpred 11.1407812 10.0976522 10.5736106 10.7425791 10.7281592 10.7657619
LNMEDHVAL 10.3766113 10.3797217 10.0432495 10.1385597 10.8723707 10.9059560
CV residual -0.7641699 0.2820696 -0.5303612 -0.6040195 0.1442115 0.1401941
[,138] [,139] [,140] [,141] [,142] [,143]
Predicted 11.0133344 10.8535369 10.5839893 10.1134559 10.259027 11.156140
cvpred 11.0080456 10.8511759 10.5874865 10.1309707 10.271953 11.140781
LNMEDHVAL 10.8117461 10.6642934 10.8016143 10.2955296 9.464983 9.769956
CV residual -0.1962995 -0.1868825 0.2141278 0.1645589 -0.806970 -1.370825
[,144] [,145] [,146] [,147] [,148] [,149]
Predicted 10.975556 10.8425381 10.83870067 10.7457044 10.3539164 10.5427886
cvpred 10.972327 10.8398461 10.83334989 10.7451274 10.3638500 10.5497496
LNMEDHVAL 9.888374 10.3254820 10.77268668 9.8469172 10.0475879 9.6290507
CV residual -1.083953 -0.5143642 -0.06066321 -0.8982102 -0.3162621 -0.9206989
[,150] [,151] [,152] [,153] [,154] [,155]
Predicted 11.0948967 11.37670 10.7579770 10.9469464 10.41031452 10.3200540
cvpred 11.0814685 11.38031 10.7574628 10.9428846 10.41934574 10.3357756
LNMEDHVAL 10.5105320 10.02127 10.1023384 10.1023384 10.38899537 9.8036672
CV residual -0.5709365 -1.35904 -0.6551243 -0.8405462 -0.03035037 -0.5321084
[,156] [,157] [,158] [,159] [,160] [,161]
Predicted 10.929584 10.495016 10.6111169 10.7003958 10.7435954 10.4574496
cvpred 10.928498 10.512857 10.6142036 10.7032047 10.7464711 10.4667269
LNMEDHVAL 9.711116 9.457200 10.2182983 10.2035921 10.3640720 10.3417425
CV residual -1.217382 -1.055656 -0.3959053 -0.4996125 -0.3823992 -0.1249844
[,162] [,163] [,164] [,165] [,166] [,167]
Predicted 11.453652 11.12653995 11.502211 10.84459870 11.1343645 11.2158095
cvpred 11.442906 11.11587047 11.492218 10.84214413 11.1215027 11.2117925
LNMEDHVAL 9.933046 11.04452056 10.388995 10.86475165 10.8493371 10.6805162
CV residual -1.509860 -0.07134992 -1.103223 0.02260752 -0.2721656 -0.5312763
[,168] [,169] [,170] [,171] [,172] [,173]
Predicted 10.6503671 10.7875006 10.74411149 11.0119706 10.3207725 10.6345433
cvpred 10.6535621 10.7863033 10.74633646 11.0027006 10.3317511 10.6403719
LNMEDHVAL 10.4772880 10.4940481 10.67590791 10.6851034 10.2219413 10.1266311
CV residual -0.1762742 -0.2922552 -0.07042855 -0.3175972 -0.1098098 -0.5137408
[,174] [,175] [,176] [,177] [,178] [,179]
Predicted 11.183331 11.2571276 10.9152946 10.6960790 11.044845 10.9225455
cvpred 11.172753 11.2433346 10.9129709 10.6980357 11.041798 10.9185918
LNMEDHVAL 9.830917 10.2989023 10.4133127 10.3545632 9.980449 10.0941079
CV residual -1.341836 -0.9444323 -0.4996582 -0.3434726 -1.061349 -0.8244839
[,180] [,181] [,182] [,183] [,184] [,185]
Predicted 10.8544394 10.3580590 10.5806296 10.8053935 10.7173673 10.2267713
cvpred 10.8510266 10.3678620 10.5916098 10.8027720 10.7176243 10.2414228
LNMEDHVAL 10.6619542 9.9987977 9.8626656 10.5050675 10.4042628 10.3672216
CV residual -0.1890724 -0.3690642 -0.7289443 -0.2977045 -0.3133614 0.1257987
[,186] [,187] [,188] [,189] [,190] [,191]
Predicted 10.7274450 10.57897792 11.6783929 10.8167402 11.08245885 11.1694144
cvpred 10.7329424 10.58181572 11.6711324 10.8120818 11.07219799 11.1603971
LNMEDHVAL 10.2470773 10.52137225 12.1399328 11.0958937 11.11095425 11.3771057
CV residual -0.4858651 -0.06044347 0.4688004 0.2838119 0.03875625 0.2167086
[,192] [,193] [,194] [,195] [,196] [,197]
Predicted 11.3614423 11.0175105 10.8842647 10.9107533 11.0163184 11.0142239
cvpred 11.3535085 11.0113575 10.8791939 10.9054865 11.0114981 11.0109813
LNMEDHVAL 11.4616322 11.3034382 11.3445068 11.2528586 11.2145194 11.3009691
CV residual 0.1081237 0.2920808 0.4653129 0.3473721 0.2030213 0.2899878
[,198] [,199] [,200] [,201] [,202] [,203]
Predicted 11.0302983 10.8377748 11.1354639 11.1904080 11.590601 11.7656055
cvpred 11.0218928 10.8353958 11.1268443 11.1819216 11.581979 11.7693300
LNMEDHVAL 11.2212354 11.1982147 11.5317472 11.6835118 13.815512 12.7656884
CV residual 0.1993425 0.3628189 0.4049029 0.5015902 2.233532 0.9963584
[,204] [,205] [,206] [,207] [,208] [,209]
Predicted 11.1580372 11.335480 11.475971 10.9723532 11.24529 11.2120494
cvpred 11.1460791 11.326870 11.471613 10.9711847 11.23396 11.1997423
LNMEDHVAL 11.8988679 12.313132 12.595408 11.3805363 11.61909 11.8699004
CV residual 0.7527888 0.986262 1.123795 0.4093516 0.38513 0.6701581
[,210] [,211] [,212] [,213] [,214] [,215]
Predicted 11.4458794 11.0906199 10.8400538 10.7048456 10.810428209 11.0040734
cvpred 11.4350133 11.0866207 10.8382719 10.7045061 10.810302409 10.9943728
LNMEDHVAL 11.9879166 11.8055951 11.2450460 10.5661755 10.817776282 10.8434948
CV residual 0.5529033 0.7189744 0.4067742 -0.1383306 0.007473873 -0.1508779
[,216] [,217] [,218] [,219] [,220]
Predicted 10.6960353 10.5901025 11.265079849 10.37331578 11.0954486
cvpred 10.6994739 10.5950168 11.251410111 10.38775079 11.0947355
LNMEDHVAL 10.3889954 10.0033329 11.242428217 10.36722157 11.3349943
CV residual -0.3104785 -0.5916839 -0.008981894 -0.02052923 0.2402587
[,221] [,222] [,223] [,224] [,225] [,226]
Predicted 10.6012108 11.1221587 10.77906098 10.73378971 10.9405383 11.1446316
cvpred 10.6066487 11.1093407 10.77918427 10.73620669 10.9358649 11.1330233
LNMEDHVAL 10.8551454 10.9041194 10.75149944 10.78931908 11.0493014 11.6699292
CV residual 0.2484968 -0.2052212 -0.02768482 0.05311239 0.1134366 0.5369059
[,227] [,228] [,229] [,230] [,231] [,232]
Predicted 11.1642380 11.6745318 11.2296162 11.042027 11.6468803 11.0752250
cvpred 11.1538999 11.6672114 11.2201668 11.035630 11.6440669 11.0648509
LNMEDHVAL 11.5149235 11.9309777 11.4721035 11.645707 12.4821881 11.7729794
CV residual 0.3610236 0.2637663 0.2519367 0.610077 0.8381212 0.7081284
[,233] [,234] [,235] [,236] [,237] [,238]
Predicted 11.4152730 11.2047276 11.7078275 11.1581713 11.10449651 10.8987245
cvpred 11.4052363 11.1901220 11.7037714 11.1478664 11.09404988 10.8943045
LNMEDHVAL 11.5463602 11.2305626 11.5038847 11.5109235 11.11691552 11.1360478
CV residual 0.1411239 0.0404406 -0.1998867 0.3630571 0.02286563 0.2417433
[,239] [,240] [,241] [,242] [,243]
Predicted 11.18429963 11.08069758 11.07392583 10.8485039 10.96844735
cvpred 11.16937724 11.06771710 11.06422410 10.8463861 10.95979572
LNMEDHVAL 11.14186178 11.10945836 11.15767807 10.5840560 11.01862914
CV residual -0.02751546 0.04174126 0.09345397 -0.2623302 0.05883342
[,244] [,245] [,246] [,247] [,248] [,249]
Predicted 10.9078914 11.09520110 11.3512713 10.98182409 11.3531289 10.9077526
cvpred 10.9030680 11.08504497 11.3389382 10.97276386 11.3408245 10.9040190
LNMEDHVAL 11.0587952 11.04132055 10.9577996 10.98698620 10.9664727 10.9150885
CV residual 0.1557272 -0.04372441 -0.3811386 0.01422235 -0.3743519 0.0110695
[,250] [,251] [,252] [,253] [,254]
Predicted 10.408057 10.8916805 10.964934813 10.9523180 10.60543494
cvpred 10.419366 10.8872514 10.957527098 10.9484702 10.61072091
LNMEDHVAL 10.915088 10.5347593 10.961277847 10.7493558 10.56874953
CV residual 0.495722 -0.3524921 0.003750749 -0.1991144 -0.04197138
[,255] [,256] [,257] [,258] [,259] [,260]
Predicted 10.90165212 10.8947850 10.4574675 10.7807775 9.361918 11.0284443
cvpred 10.89431660 10.8884338 10.4653733 10.7793438 9.403127 11.0195338
LNMEDHVAL 10.79753268 10.4072886 10.8395809 10.5635949 10.714418 10.1619982
CV residual -0.09678392 -0.4811453 0.3742076 -0.2157489 1.311291 -0.8575356
[,261] [,262] [,263] [,264] [,265] [,266]
Predicted 10.9818250 11.0676378 10.8941805 11.0007159 10.9556728 11.07390828
cvpred 10.9748226 11.0606970 10.8887569 10.9928628 10.9497827 11.06727232
LNMEDHVAL 10.6310362 10.4163112 10.6358554 10.6501755 10.7054891 11.04132055
CV residual -0.3437865 -0.6443858 -0.2529014 -0.3426873 -0.2442935 -0.02595176
[,267] [,268] [,269] [,270] [,271]
Predicted 11.04186202 10.74082607 10.7846427 10.96306368 10.9418864
cvpred 11.03010595 10.74285243 10.7865273 10.95438800 10.9346534
LNMEDHVAL 11.07286891 10.68510338 11.0169885 10.90043619 10.2146420
CV residual 0.04276297 -0.05774904 0.2304612 -0.05395181 -0.7200114
[,272] [,273] [,274] [,275] [,276] [,277]
Predicted 10.77861132 10.6402813 10.8071988 10.9717364 10.7407839 10.9245822
cvpred 10.78336454 10.6444873 10.8042036 10.9621913 10.7404250 10.9192058
LNMEDHVAL 10.77268668 10.0168162 10.4370527 10.5532052 10.5078035 10.5815211
CV residual -0.01067786 -0.6276711 -0.3671509 -0.4089861 -0.2326215 -0.3376847
[,278] [,279] [,280] [,281] [,282]
Predicted 10.6909070 11.0582502 11.2521375 11.134573441 10.9418728
cvpred 10.6914548 11.0496839 11.2395217 11.122893646 10.9364433
LNMEDHVAL 10.5687495 10.8985895 11.4563551 11.128732492 11.1169155
CV residual -0.1227053 -0.1510944 0.2168335 0.005838846 0.1804722
[,283] [,284] [,285] [,286] [,287]
Predicted 11.28198422 10.96202278 11.05148996 10.95707320 10.99808857
cvpred 11.26857661 10.95278389 11.03943034 10.94860488 10.98917349
LNMEDHVAL 11.31080928 11.00708738 10.97507117 10.96819829 11.04930144
CV residual 0.04223267 0.05430349 -0.06435917 0.01959341 0.06012795
[,288] [,289] [,290] [,291] [,292]
Predicted 10.98172308 10.98857660457 11.094654585 10.9182675 10.9616441
cvpred 10.97186308 10.97850052148 11.084042950 10.9110905 10.9529903
LNMEDHVAL 11.04132055 10.97848997557 11.091330975 11.1490820 11.1968439
CV residual 0.06945748 -0.00001054591 0.007288024 0.2379915 0.2438536
[,293] [,294] [,295] [,296] [,297] [,298]
Predicted 11.140064 11.0817857 11.051106 10.92767899 10.98750048 11.005089335
cvpred 11.126512 11.0692524 11.039058 10.91952289 10.97745833 10.995375620
LNMEDHVAL 11.268303 11.1732481 11.187195 10.98867682 11.03003921 10.997087299
CV residual 0.141791 0.1039957 0.148137 0.06915393 0.05258088 0.001711679
[,299] [,300] [,301] [,302] [,303]
Predicted 10.97292311 11.04202709 11.10649630 11.02271319 11.1969168
cvpred 10.96436716 11.03026581 11.09493340 11.01321931 11.1821900
LNMEDHVAL 10.93667204 10.99541085 11.02353512 10.93667204 10.9384498
CV residual -0.02769513 -0.03485496 -0.07139828 -0.07654727 -0.2437402
[,304] [,305] [,306] [,307] [,308] [,309]
Predicted 10.80085565 11.0285012 11.2951105 10.8993421 11.46895 10.96962828
cvpred 10.80061754 11.0179975 11.2819064 10.8957931 11.45844 10.96139765
LNMEDHVAL 10.85514543 10.8723707 11.2036792 11.0821425 10.25414 11.02353512
CV residual 0.05452789 -0.1456267 -0.0782272 0.1863495 -1.20430 0.06213747
[,310] [,311] [,312] [,313] [,314] [,315]
Predicted 11.15614028 11.0256743 11.1013058 11.2211255 11.1736645 11.063826
cvpred 11.14078123 11.0149901 11.0876755 11.2117305 11.1640844 11.058658
LNMEDHVAL 11.12136326 11.2239092 11.2972539 11.5028751 11.3713619 11.461632
CV residual -0.01941796 0.2089191 0.2095784 0.2911447 0.2072775 0.402974
[,316] [,317] [,318] [,319] [,320] [,321]
Predicted 11.4035904 11.3499273 11.3033888 11.4163158 11.115173 11.1334273
cvpred 11.3968210 11.3395842 11.2936148 11.4093120 11.107132 11.1222902
LNMEDHVAL 11.6064158 11.4906799 11.6181860 11.6877188 11.470018 11.3302038
CV residual 0.2095948 0.1510957 0.3245712 0.2784067 0.362886 0.2079136
[,322] [,323] [,324] [,325] [,326] [,327]
Predicted 11.0444608 11.0972010 11.95664352 11.5776816 12.0274114 11.0133983
cvpred 11.0331944 11.0844619 11.95614539 11.5728504 12.0255631 11.0043576
LNMEDHVAL 11.4414295 11.5119250 11.85934803 11.4804023 11.4489201 11.4306302
CV residual 0.4082351 0.4274631 -0.09679736 -0.0924481 -0.5766429 0.4262726
[,328] [,329] [,330] [,331] [,332] [,333]
Predicted 11.0442500 11.0008425 11.05972 11.1561403 11.2237746 11.2186746
cvpred 11.0362971 10.9936456 11.04964 11.1407812 11.2132928 11.2104108
LNMEDHVAL 11.1462002 11.2318879 11.35977 11.3241833 11.4489201 11.5159210
CV residual 0.1099031 0.2382423 0.31013 0.1834021 0.2356273 0.3055102
[,334] [,335] [,336] [,337] [,338] [,339]
Predicted 11.5358686 11.2786048 11.99767276 11.56323755 11.2549540 11.0688477
cvpred 11.5312855 11.2686266 11.99536326 11.55872728 11.2452154 11.0567897
LNMEDHVAL 11.8649898 11.5307654 11.95375772 11.62625415 11.5502212 11.3884954
CV residual 0.3337043 0.2621388 -0.04160554 0.06752687 0.3050058 0.3317057
[,340] [,341] [,342] [,343] [,344]
Predicted 11.1561403 11.2415845 11.0387273 11.0751414 11.174525
cvpred 11.1407812 11.2275505 11.0274977 11.0653634 11.159451
LNMEDHVAL 11.3759596 11.5038847 11.3828168 11.2935249 12.318508
CV residual 0.2351784 0.2763343 0.3553191 0.2281615 1.159057
Sum of squares = 103.89 Mean square = 0.3 n = 344
fold 4
Observations in test set: 344
[,1] [,2] [,3] [,4] [,5] [,6]
Predicted 10.910125 10.8826184 10.9764695 10.881929 10.99222 11.1561403
cvpred 10.910243 10.8826199 10.9773531 10.882044 10.99277 11.1573026
LNMEDHVAL 11.640439 10.7144178 11.9427579 12.360080 12.46265 11.9984333
CV residual 0.730196 -0.1682022 0.9654049 1.478036 1.46988 0.8411307
[,7] [,8] [,9] [,10] [,11] [,12]
Predicted 10.998417 11.038668 10.6876353 10.8299667 10.6242291 10.5098554
cvpred 10.999676 11.039899 10.6881880 10.8303710 10.6234120 10.5082749
LNMEDHVAL 12.149502 12.483704 11.1139393 11.7913145 11.3433227 10.9869862
CV residual 1.149826 1.443806 0.4257513 0.9609435 0.7199107 0.4787113
[,13] [,14] [,15] [,16] [,17] [,18]
Predicted 10.7672765 10.7530505 10.4458175 10.2968294 10.75857838 10.9773785
cvpred 10.7685542 10.7528781 10.4451778 10.2948749 10.75885993 10.9782710
LNMEDHVAL 11.1004357 11.6217799 10.7232674 10.8666619 10.78311430 11.3326019
CV residual 0.3318816 0.8689018 0.2780896 0.5717869 0.02425437 0.3543309
[,19] [,20] [,21] [,22] [,23] [,24]
Predicted 11.1000174 10.243180 10.5988782 10.99078203 11.0461262 10.96631127
cvpred 11.1024257 10.242131 10.5976755 10.99156009 11.0482019 10.96705305
LNMEDHVAL 11.2091140 10.860920 11.4008760 11.05247605 11.1533893 10.95430918
CV residual 0.1066883 0.618789 0.8032004 0.06091596 0.1051874 -0.01274387
[,25] [,26] [,27] [,28] [,29] [,30]
Predicted 10.81761225 10.7008888 10.9402991 10.8966356 10.3022649 10.7596821
cvpred 10.81778311 10.7017731 10.9422919 10.8982331 10.3009067 10.7600615
LNMEDHVAL 10.74289724 10.3703613 10.2681307 9.8984750 10.9277354 10.6334487
CV residual -0.07488587 -0.3314118 -0.6741613 -0.9997581 0.6268288 -0.1266128
[,31] [,32] [,33] [,34] [,35] [,36]
Predicted 11.0059018 10.9737055 10.91766377 10.7749685 10.91956322 11.1561403
cvpred 11.0067313 10.9742984 10.91781402 10.7761544 10.92074431 11.1573026
LNMEDHVAL 10.4544950 11.3361883 10.87993221 10.1961572 10.89302875 10.9595402
CV residual -0.5522364 0.3618899 -0.03788181 -0.5799972 -0.02771556 -0.1977624
[,37] [,38] [,39] [,40] [,41]
Predicted 10.90002736 10.87779248 10.9810339 11.09242714 11.1448588
cvpred 10.90118609 10.87798303 10.9822696 11.09356968 11.1463320
LNMEDHVAL 10.87615862 10.80161431 10.8609202 11.18580932 11.7174976
CV residual -0.02502748 -0.07636872 -0.1213493 0.09223964 0.5711656
[,42] [,43] [,44] [,45] [,46] [,47]
Predicted 11.0733298 11.17876513 10.9981767 10.985921 10.9150342 10.9424801
cvpred 11.0741407 11.18340938 10.9992761 10.987058 10.9157565 10.9453477
LNMEDHVAL 11.7973522 11.15338929 11.3349943 10.689670 10.7099634 10.4829060
CV residual 0.7232115 -0.03002009 0.3357182 -0.297388 -0.2057931 -0.4624417
[,48] [,49] [,50] [,51] [,52] [,53]
Predicted 10.3594523 10.7507100 11.0257363 10.7759728 10.8817200 10.7052778
cvpred 10.3583351 10.7509953 11.0292659 10.7759813 10.8819388 10.7053923
LNMEDHVAL 10.7536385 10.5159668 10.5294260 10.4012279 10.8137602 10.6873891
CV residual 0.3953034 -0.2350284 -0.4998399 -0.3747534 -0.0681786 -0.0180032
[,54] [,55] [,56] [,57] [,58] [,59]
Predicted 10.4258516 10.5031044 11.0756435 10.8721545 10.7735450 10.4713667
cvpred 10.4247781 10.5043185 11.0783781 10.8726340 10.7737493 10.4700367
LNMEDHVAL 10.5453414 10.6896696 10.4487146 10.6689554 10.4995730 9.8678604
CV residual 0.1205634 0.1853511 -0.6296635 -0.2036786 -0.2741763 -0.6021763
[,60] [,61] [,62] [,63] [,64] [,65]
Predicted 10.8707140 10.8411152 10.619514146 10.392146 11.299869 10.199838
cvpred 10.8710708 10.8425725 10.619440513 10.390565 11.303886 10.196941
LNMEDHVAL 10.6572594 10.5400644 10.628617779 10.633449 10.354563 10.613983
CV residual -0.2138114 -0.3025081 0.009177266 0.242884 -0.949323 0.417042
[,66] [,67] [,68] [,69] [,70] [,71]
Predicted 10.30110778 10.8332439 10.5954114 10.6678853 10.8785677 10.8176412
cvpred 10.29893738 10.8330358 10.5950321 10.6681743 10.8792374 10.8177092
LNMEDHVAL 10.24707726 10.9490506 10.8077057 10.5661755 10.4829060 10.6454249
CV residual -0.05186013 0.1160148 0.2126736 -0.1019988 -0.3963314 -0.1722843
[,72] [,73] [,74] [,75] [,76] [,77]
Predicted 10.8796599 10.8302991 10.6555419 10.7503431 10.63382296 10.8003413
cvpred 10.8799252 10.8302992 10.6566151 10.7503312 10.63323317 10.7999936
LNMEDHVAL 10.7342204 10.6525424 10.5159668 11.1331281 10.61152335 11.3997568
CV residual -0.1457048 -0.1777568 -0.1406482 0.3827969 -0.02170983 0.5997632
[,78] [,79] [,80] [,81] [,82] [,83]
Predicted 10.378308 11.0604915 11.1895777 11.0719712 11.000122 10.54611340
cvpred 10.376170 11.0625569 11.1914041 11.0727763 11.000622 10.54468677
LNMEDHVAL 11.461632 11.3736634 11.3302038 11.5588544 12.221454 10.56617553
CV residual 1.085462 0.3111065 0.1387997 0.4860781 1.220832 0.02148875
[,84] [,85] [,86] [,87] [,88] [,89]
Predicted 10.1758736 10.8135810 10.40628443 10.6757848 10.43660943 10.9237393
cvpred 10.1733065 10.8153057 10.40426436 10.6759797 10.43471806 10.9245967
LNMEDHVAL 10.3889954 10.4829060 10.38899537 10.5479696 10.41930072 10.2921455
CV residual 0.2156889 -0.3323997 -0.01526899 -0.1280102 -0.01541735 -0.6324512
[,90] [,91] [,92] [,93] [,94] [,95]
Predicted 11.0613825 11.2889100 10.7956284 10.6352199 10.8071971 10.9126768
cvpred 11.0628399 11.2927092 10.7958274 10.6357257 10.8072543 10.9128059
LNMEDHVAL 11.1760531 11.0332755 10.9114455 10.2363820 10.9077892 10.7913788
CV residual 0.1132132 -0.2594337 0.1156181 -0.3993438 0.1005348 -0.1214271
[,96] [,97] [,98] [,99] [,100] [,101]
Predicted 10.7411003 10.25115804 10.393886 10.4878474 10.3067636 10.524945088
cvpred 10.7415308 10.24847960 10.393360 10.4861734 10.3051460 10.526110503
LNMEDHVAL 10.4042628 10.32219789 10.633449 10.0212706 10.0388922 10.524064040
CV residual -0.3372679 0.07371828 0.240089 -0.4649029 -0.2662538 -0.002046463
[,102] [,103] [,104] [,105] [,106]
Predicted 10.8828470 10.5838538 10.79064348 11.06893892 10.85470194
cvpred 10.8828495 10.5825873 10.79025465 11.07068681 10.85486038
LNMEDHVAL 10.4516090 10.7009947 10.73203937 11.09589372 10.94022444
CV residual -0.4312405 0.1184074 -0.05821528 0.02520691 0.08536406
[,107] [,108] [,109] [,110] [,111] [,112]
Predicted 10.9232053 11.06712498 10.9634110 10.9132006 11.4414088 11.0176001
cvpred 10.9239425 11.06847021 10.9649693 10.9133319 11.4482366 11.0181745
LNMEDHVAL 11.1899616 11.11988288 11.1619485 11.0235351 11.9563284 11.4392789
CV residual 0.2660191 0.05141266 0.1969792 0.1102032 0.5080918 0.4211044
[,113] [,114] [,115] [,116] [,117] [,118]
Predicted 11.1561403 10.056793 11.1561403 11.1617217 10.670645 10.889523
cvpred 11.1573026 10.057319 11.1573026 11.1641152 10.669747 10.889554
LNMEDHVAL 11.3504065 11.233212 11.3083583 11.2332116 11.386228 12.611538
CV residual 0.1931039 1.175893 0.1510557 0.0690964 0.716481 1.721984
[,119] [,120] [,121] [,122] [,123] [,124]
Predicted 10.991665 10.945514 10.70347374 10.9650892 11.0107996 10.973542
cvpred 10.992130 10.949006 10.70487665 10.9654408 11.0119314 10.975584
LNMEDHVAL 12.148973 10.221941 10.72985358 11.6199845 11.7814247 10.344963
CV residual 1.156843 -0.727065 0.02497693 0.6545438 0.7694933 -0.630621
[,125] [,126] [,127] [,128] [,129] [,130]
Predicted 10.0926402 10.0859537 9.9280944 10.531995 11.0064040 11.0864314
cvpred 10.0898137 10.0837525 9.9270443 10.530676 11.0069309 11.0922971
LNMEDHVAL 10.9150885 9.5539301 9.5178251 9.769956 10.7099634 10.6572594
CV residual 0.8252747 -0.5298224 -0.4092193 -0.760720 -0.2969675 -0.4350377
[,131] [,132] [,133] [,134] [,135] [,136]
Predicted 10.9180454 10.73211635 11.1226440 10.7237850 11.1561403 10.57009914
cvpred 10.9189279 10.73229327 11.1242468 10.7244724 11.1573026 10.56877431
LNMEDHVAL 11.1633680 10.79957558 11.0332755 10.2819240 11.2158662 10.48010092
CV residual 0.2444401 0.06728231 -0.0909713 -0.4425484 0.0585636 -0.08867339
[,137] [,138] [,139] [,140] [,141] [,142]
Predicted 10.578641 10.37948017 10.4589082 10.4910514 11.156140 10.45753755
cvpred 10.578630 10.37870564 10.4582651 10.4903203 11.157303 10.45664997
LNMEDHVAL 9.464983 10.41930072 10.7472076 10.3320179 10.021271 10.37661131
CV residual -1.113647 0.04059508 0.2889425 -0.1583023 -1.136032 -0.08003866
[,143] [,144] [,145] [,146] [,147] [,148]
Predicted 11.3386140 10.9311018 10.5418933 10.30568006 10.8509094 10.8902680
cvpred 11.3434003 10.9318988 10.5408509 10.30351654 10.8507763 10.8908206
LNMEDHVAL 10.9869862 10.7995756 10.8376182 10.38899537 10.5865844 10.6596095
CV residual -0.3564141 -0.1323233 0.2967673 0.08547882 -0.2641919 -0.2312111
[,149] [,150] [,151] [,152] [,153] [,154]
Predicted 10.84175019 10.3764738 10.8329100 10.8319994 10.4015704 10.865153
cvpred 10.84197997 10.3755950 10.8337367 10.8335523 10.3995304 10.865080
LNMEDHVAL 10.79548559 10.1345993 10.1658518 9.8626656 9.5609972 9.764225
CV residual -0.04649438 -0.2409957 -0.6678849 -0.9708868 -0.8385331 -1.100855
[,155] [,156] [,157] [,158] [,159] [,160]
Predicted 10.611357 10.862541 11.132693 8.736440 10.8352089 10.463782
cvpred 10.613503 10.864685 11.134570 8.727776 10.8362542 10.462006
LNMEDHVAL 9.539644 9.698920 9.602382 10.221941 10.2435249 9.975808
CV residual -1.073858 -1.165765 -1.532188 1.494165 -0.5927293 -0.486198
[,161] [,162] [,163] [,164] [,165] [,166]
Predicted 10.2311498 11.069762 10.1750791 10.6771357 10.6921650 10.5785306
cvpred 10.2283865 11.070558 10.1728187 10.6771794 10.6930276 10.5776589
LNMEDHVAL 9.5324239 9.510445 9.9330464 9.9475044 9.9134379 10.2109723
CV residual -0.6959626 -1.560113 -0.2397723 -0.7296749 -0.7795897 -0.3666866
[,167] [,168] [,169] [,170] [,171] [,172]
Predicted 11.0193719 10.903927 10.686565 11.121080 10.133311 10.7543851
cvpred 11.0205151 10.905071 10.686524 11.122648 10.130530 10.7558543
LNMEDHVAL 10.4042628 10.236382 9.642123 9.717158 9.602382 9.9522777
CV residual -0.6162523 -0.668689 -1.044401 -1.405490 -0.528148 -0.8035765
[,173] [,174] [,175] [,176] [,177] [,178]
Predicted 10.5868102 10.6168521 10.5515753 10.791933 10.8925003 10.7491668
cvpred 10.5865799 10.6167249 10.5512396 10.794643 10.8930834 10.7486020
LNMEDHVAL 10.2819240 9.9281802 10.3481734 9.752665 10.6782147 10.4222813
CV residual -0.3046559 -0.6885448 -0.2030662 -1.041978 -0.2148687 -0.3263206
[,179] [,180] [,181] [,182] [,183]
Predicted 11.223047 10.81407053 10.826342314 11.1465723 10.94149350
cvpred 11.225538 10.81378112 10.826659190 11.1504436 10.94282201
LNMEDHVAL 9.740969 10.79957558 10.821776287 10.2435249 10.96647266
CV residual -1.484570 -0.01420554 -0.004882903 -0.9069188 0.02365065
[,184] [,185] [,186] [,187] [,188] [,189]
Predicted 11.06485431 10.9837737 11.0843600 10.9236131 11.2096124 11.1498705
cvpred 11.06596712 10.9842046 11.0872694 10.9253555 11.2118367 11.1523936
LNMEDHVAL 11.08214255 10.9437643 10.9205282 10.5840560 10.8277465 10.8742665
CV residual 0.01617543 -0.0404403 -0.1667412 -0.3412995 -0.3840902 -0.2781272
[,190] [,191] [,192] [,193] [,194] [,195]
Predicted 11.0235838 10.8516290 11.2317510 11.0104528 11.0519150 10.83673370
cvpred 11.0244897 10.8535476 11.2344150 11.0114950 11.0535341 10.83743396
LNMEDHVAL 10.4341158 10.6382564 10.8985895 10.7934343 10.8473935 10.76214917
CV residual -0.5903739 -0.2152912 -0.3358255 -0.2180607 -0.2061407 -0.07528479
[,196] [,197] [,198] [,199] [,200] [,201]
Predicted 11.1861297 10.8371150 10.7545215 10.7368819 10.9510941 10.7223480
cvpred 11.1904665 10.8380463 10.7573352 10.7362649 10.9530601 10.7226408
LNMEDHVAL 10.7099634 10.4163112 10.2576594 10.3385115 10.3089527 10.2255711
CV residual -0.4805031 -0.4217351 -0.4996759 -0.3977534 -0.6441074 -0.4970697
[,202] [,203] [,204] [,205] [,206] [,207]
Predicted 10.8607837 10.7262703 10.60468432 9.8991651 10.5503434 10.7384564
cvpred 10.8611813 10.7257803 10.60407872 9.8949928 10.5506208 10.7378461
LNMEDHVAL 10.2255711 9.9804486 10.68510338 9.7925560 10.4282161 10.1581298
CV residual -0.6356102 -0.7453317 0.08102466 -0.1024368 -0.1224048 -0.5797163
[,208] [,209] [,210] [,211] [,212] [,213]
Predicted 10.6622143 11.093001 10.7891023 11.0067601 11.0504093 11.1561403
cvpred 10.6623424 11.095515 10.7894411 11.0079600 11.0512140 11.1573026
LNMEDHVAL 10.0899671 12.251046 11.2541547 11.2593227 11.4574128 11.6307085
CV residual -0.5723753 1.155531 0.4647137 0.2513627 0.4061988 0.4734059
[,214] [,215] [,216] [,217] [,218] [,219]
Predicted 11.27915588 11.1036571 11.23334036 11.1733191 11.074787 11.2623911
cvpred 11.28276132 11.1051904 11.23603591 11.1766150 11.076989 11.2656636
LNMEDHVAL 11.25156070 11.3816772 11.20095070 11.6342578 11.542484 11.4710613
CV residual -0.03120062 0.2764868 -0.03508521 0.4576427 0.465495 0.2053977
[,220] [,221] [,222] [,223] [,224] [,225]
Predicted 11.63942477 11.378371 11.801835 11.1530415 10.4653875 10.9997265
cvpred 11.65018515 11.386247 11.817288 11.1566356 10.4646283 11.0008726
LNMEDHVAL 11.72399644 12.888664 12.846346 11.9381932 11.3302038 11.2502612
CV residual 0.07381128 1.502417 1.029059 0.7815576 0.8655756 0.2493885
[,226] [,227] [,228] [,229] [,230] [,231]
Predicted 10.6940560 10.9566529 10.6675856 11.0127391 11.107737 10.704405
cvpred 10.6952402 10.9591918 10.6674724 11.0163204 11.109389 10.704163
LNMEDHVAL 10.8551454 11.6613455 10.9114455 10.5687495 10.760028 11.013699
CV residual 0.1599052 0.7021536 0.2439731 -0.4475709 -0.349361 0.309536
[,232] [,233] [,234] [,235] [,236] [,237]
Predicted 10.9399639 10.8737596 10.81588298 10.5506185 10.5646864 11.1368835
cvpred 10.9402088 10.8752542 10.81679895 10.5504298 10.5643981 11.1405051
LNMEDHVAL 10.5865844 10.6188853 10.83565163 10.8551454 10.8097279 11.0348897
CV residual -0.3536244 -0.2563689 0.01885268 0.3047156 0.2453299 -0.1056154
[,238] [,239] [,240] [,241] [,242] [,243]
Predicted 10.8694193 10.84976784 10.5538177 10.98242434 11.2439662 11.2689419
cvpred 10.8693648 10.85190954 10.5524237 10.98357634 11.2504367 11.2723445
LNMEDHVAL 10.5916222 10.83368119 10.7363967 10.96474405 11.6100522 11.8600550
CV residual -0.2777426 -0.01822835 0.1839729 -0.01883228 0.3596155 0.5877105
[,244] [,245] [,246] [,247] [,248] [,249]
Predicted 10.9563607 11.2694158 11.10799792 10.8010868 11.05110701 11.0643147
cvpred 10.9575325 11.2741646 11.10939660 10.8011514 11.05205402 11.0659509
LNMEDHVAL 11.6977439 11.7248058 11.19958365 11.3702092 11.14764215 11.2332116
CV residual 0.7402114 0.4506412 0.09018704 0.5690577 0.09558813 0.1672607
[,250] [,251] [,252] [,253] [,254] [,255]
Predicted 11.1843149 11.1857841 11.1063103 10.95911526 11.03769404 11.2159679
cvpred 11.1877678 11.1875351 11.1087270 10.95998419 11.03835370 11.2183185
LNMEDHVAL 11.4957793 11.4499857 11.4499857 11.02026715 11.11393932 10.7851868
CV residual 0.3080115 0.2624505 0.3412587 0.06028296 0.07558563 -0.4331316
[,256] [,257] [,258] [,259] [,260] [,261]
Predicted 10.94749655 10.9339059 11.15614028 10.9060914 11.2518454 11.4044984
cvpred 10.94829832 10.9345682 11.15730263 10.9069144 11.2581350 11.4129711
LNMEDHVAL 10.92413830 11.1619485 11.10043574 11.0202671 11.7248058 11.6036798
CV residual -0.02416002 0.2273804 -0.05686689 0.1133528 0.4666708 0.1907087
[,262] [,263] [,264] [,265] [,266]
Predicted 11.19843587 11.2035360 10.90143273 10.9538705 10.97237757
cvpred 11.20043821 11.2056396 10.90251250 10.9551404 10.97330912
LNMEDHVAL 11.24635236 10.8609202 10.84153978 10.8376182 10.93131966
CV residual 0.04591414 -0.3447194 -0.06097272 -0.1175222 -0.04198946
[,267] [,268] [,269] [,270] [,271] [,272]
Predicted 10.8287630 10.9720842 10.9069394 10.884101346 10.6936459 11.0833927
cvpred 10.8294264 10.9734755 10.9076140 10.885296442 10.6954644 11.0861566
LNMEDHVAL 11.0666384 10.6382564 10.5347593 10.894885757 10.4857032 10.6139834
CV residual 0.2372119 -0.3352191 -0.3728547 0.009589315 -0.2097612 -0.4721732
[,273] [,274] [,275] [,276] [,277]
Predicted 10.9250062 11.2872227 10.75147209736 11.0309707 11.1046703
cvpred 10.9267533 11.2929419 10.75151837966 11.0332380 11.1063949
LNMEDHVAL 10.5050675 10.7385682 10.75149944366 10.6237634 10.9801950
CV residual -0.4216858 -0.5543737 -0.00001893601 -0.4094746 -0.1261999
[,278] [,279] [,280] [,281] [,282] [,283]
Predicted 10.95509672 10.9585494 11.242011 10.8621287 10.6826616 10.7936810
cvpred 10.95674154 10.9602230 11.244878 10.8646561 10.6837011 10.7941767
LNMEDHVAL 10.85899900 10.8177763 11.452113 10.6016223 10.3828225 10.7663775
CV residual -0.09774254 -0.1424467 0.207235 -0.2630338 -0.3008786 -0.0277992
[,284] [,285] [,286] [,287] [,288] [,289]
Predicted 10.7370031 11.0615698 11.15453680 11.217689 10.99253917 11.1046592
cvpred 10.7380025 11.0657017 11.15626454 11.220073 10.99391085 11.1062455
LNMEDHVAL 10.5764320 10.9612778 11.22524339 10.927735 10.97678203 11.0004318
CV residual -0.1615704 -0.1044238 0.06897885 -0.292338 -0.01712881 -0.1058137
[,290] [,291] [,292] [,293] [,294]
Predicted 11.09559786 11.53332084 11.2269109 11.70888888 11.2236309
cvpred 11.09866626 11.54197400 11.2313398 11.72102882 11.2261337
LNMEDHVAL 11.18303154 11.49577931 11.3702092 11.66478781 11.3492294
CV residual 0.08436529 -0.04619469 0.1388694 -0.05624101 0.1230957
[,295] [,296] [,297] [,298] [,299]
Predicted 11.03427819 10.98399278 10.98336606 11.08020904 10.98499507
cvpred 11.03639492 10.98442453 10.98433372 11.08174413 10.98636365
LNMEDHVAL 10.94729160 10.95779958 11.04132055 11.01369898 10.92773543
CV residual -0.08910331 -0.02662494 0.05698683 -0.06804515 -0.05862822
[,300] [,301] [,302] [,303] [,304]
Predicted 11.1561403 10.99046220 11.024312342 11.11888784 11.2077840
cvpred 11.1573026 10.99092140 11.026339963 11.12025355 11.2099720
LNMEDHVAL 11.0381103 10.97335737 11.021902469 11.06350847 11.0882775
CV residual -0.1191924 -0.01756403 -0.004437495 -0.05674508 -0.1216945
[,305] [,306] [,307] [,308] [,309]
Predicted 11.038833644 10.9465825 11.08413757 10.9012617 11.1069244
cvpred 11.039498142 10.9468555 11.08597296 10.9013423 11.1078779
LNMEDHVAL 11.049301443 11.2997322 11.17605315 11.2198958 10.9384498
CV residual 0.009803301 0.3528767 0.09008019 0.3185535 -0.1694281
[,310] [,311] [,312] [,313] [,314]
Predicted 11.2711616 10.98531349 11.05297961 10.87613833 10.916121666
cvpred 11.2762022 10.98669439 11.05686363 10.87716368 10.916804466
LNMEDHVAL 10.9954109 10.97164063 11.03971670 10.79343431 10.918718232
CV residual -0.2807913 -0.01505376 -0.01714693 -0.08372937 0.001913766
[,315] [,316] [,317] [,318] [,319] [,320]
Predicted 11.0380395 10.9215439 10.88806995 11.0579696 11.3065121 11.3255574
cvpred 11.0410282 10.9220328 10.88984002 11.0594652 11.3124340 11.3318036
LNMEDHVAL 11.2631812 11.1213633 10.93844981 11.1802460 11.5018645 11.5199011
CV residual 0.2221531 0.1993305 0.04860979 0.1207808 0.1894305 0.1880975
[,321] [,322] [,323] [,324] [,325] [,326]
Predicted 11.3791634 11.0790666 11.1680722 11.2178808 11.1290081 11.035706
cvpred 11.3847549 11.0810416 11.1731350 11.2226728 11.1301672 11.038954
LNMEDHVAL 11.4626842 11.3445068 11.4637352 11.5559850 11.4700180 11.440355
CV residual 0.0779293 0.2634652 0.2906002 0.3333122 0.3398507 0.401401
[,327] [,328] [,329] [,330] [,331] [,332]
Predicted 11.7690833 12.06850907 11.1555157 11.5579060 10.8775327 11.31556018
cvpred 11.7824187 12.08779108 11.1576408 11.5678972 10.8783473 11.32173262
LNMEDHVAL 11.5385932 12.03765399 11.5159210 11.3748122 10.9784900 11.36789969
CV residual -0.2438255 -0.05013709 0.3582802 -0.1930851 0.1001427 0.04616707
[,333] [,334] [,335] [,336] [,337] [,338]
Predicted 11.4839748 11.0762739 10.8888212 11.0903815 11.1939858 10.9930192
cvpred 11.4938414 11.0775163 10.8888490 11.0916149 11.1974329 10.9935822
LNMEDHVAL 11.6190857 11.3456895 11.4338823 11.3805363 11.5444241 11.4689736
CV residual 0.1252443 0.2681732 0.5450332 0.2889214 0.3469912 0.4753914
[,339] [,340] [,341] [,342] [,343] [,344]
Predicted 11.0310297 10.8751897 12.0463759 11.509860 11.0273437 11.2300383
cvpred 11.0322310 10.8758891 12.0652184 11.519043 11.0286081 11.2352434
LNMEDHVAL 11.4119995 11.4403548 11.5768388 11.664788 11.3562717 11.8277362
CV residual 0.3797686 0.5644657 -0.4883796 0.145745 0.3276636 0.5924928
Sum of squares = 86.03 Mean square = 0.25 n = 344
fold 5
Observations in test set: 344
[,1] [,2] [,3] [,4] [,5] [,6]
Predicted 10.840169 10.8469954 10.776780 10.8629626 10.648265 10.843082
cvpred 10.834374 10.8352212 10.765661 10.8514534 10.636594 10.832147
LNMEDHVAL 12.323856 11.7456232 12.177673 10.6873891 12.323856 12.885121
CV residual 1.489482 0.9104021 1.412012 -0.1640643 1.687262 2.052974
[,7] [,8] [,9] [,10] [,11] [,12]
Predicted 10.814198 10.75789 11.162298 10.891887 11.2138567 10.756312
cvpred 10.802353 10.74517 11.156802 10.882618 11.2115766 10.743033
LNMEDHVAL 11.844385 12.00823 12.278858 12.487485 12.0100578 12.261034
CV residual 1.042032 1.26306 1.122056 1.604867 0.7984812 1.518001
[,13] [,14] [,15] [,16] [,17] [,18]
Predicted 10.9483838 10.981154 10.533324 10.97834453 10.6072275 10.67915229
cvpred 10.9407387 10.974528 10.518683 10.97449069 10.5980746 10.67140810
LNMEDHVAL 11.4927228 12.048249 11.982929 10.98867682 10.4103052 10.71441777
CV residual 0.5519841 1.073721 1.464246 0.01418613 -0.1877695 0.04300967
[,19] [,20] [,21] [,22] [,23] [,24]
Predicted 10.6832815 10.0774902 10.7284919 11.10882770 10.1046216 10.5072276
cvpred 10.6722092 10.0544137 10.7200065 11.10638572 10.0805239 10.4932768
LNMEDHVAL 11.0493014 9.8362788 11.1548209 11.03650127 11.0169885 11.2050407
CV residual 0.3770923 -0.2181349 0.4348144 -0.06988445 0.9364645 0.7117639
[,25] [,26] [,27] [,28] [,29]
Predicted 11.19958637 10.80122198 10.7463321 10.54737703 10.7766801
cvpred 11.19622767 10.79145937 10.7328869 10.53369166 10.7705315
LNMEDHVAL 11.22524339 10.87804719 10.8628378 10.61398337 10.5186732
CV residual 0.02901573 0.08658783 0.1299509 0.08029171 -0.2518583
[,30] [,31] [,32] [,33] [,34] [,35]
Predicted 10.9297889 10.9601933 10.6836266 10.745594 10.6239851 10.4260184
cvpred 10.9232931 10.9604898 10.6770799 10.739645 10.6096489 10.4095217
LNMEDHVAL 11.0267925 10.4282161 10.1345993 10.510532 10.2435249 9.7981270
CV residual 0.1034994 -0.5322737 -0.5424807 -0.229113 -0.3661241 -0.6113947
[,36] [,37] [,38] [,39] [,40] [,41]
Predicted 10.8760846 10.5179670 10.4210691 9.9577367 11.0801059 11.03635127
cvpred 10.8666828 10.5024447 10.4068182 9.9335236 11.0747159 11.02772039
LNMEDHVAL 10.3577428 9.9232902 10.0212706 9.4414521 10.8647517 11.00542763
CV residual -0.5089399 -0.5791545 -0.3855476 -0.4920715 -0.2099643 -0.02229276
[,42] [,43] [,44] [,45] [,46] [,47]
Predicted 10.73445032 10.7291766 10.6488192 11.0064137 11.1108451 10.87519307
cvpred 10.72080788 10.7188537 10.6357669 10.9981506 11.1073817 10.86803215
LNMEDHVAL 10.70099475 10.4341158 10.5991316 10.8532131 11.2292354 10.91326863
CV residual -0.01981313 -0.2847379 -0.0366353 -0.1449376 0.1218538 0.04523648
[,48] [,49] [,50] [,51] [,52]
Predicted 11.030112972 10.9401745 11.0607679 11.02461462 11.064063039
cvpred 11.023546781 10.9325842 11.0548982 11.01709084 11.056997151
LNMEDHVAL 11.016988454 11.1139393 11.3314036 10.98019501 11.050890005
CV residual -0.006558327 0.1813551 0.2765054 -0.03689584 -0.006107145
[,53] [,54] [,55] [,56] [,57] [,58]
Predicted 10.8808260 10.84365 10.8802244 11.1013032 11.22489990 10.7114712
cvpred 10.8735936 10.83617 10.8698368 11.1181075 11.22462832 10.7042758
LNMEDHVAL 10.6115233 10.65018 10.9716406 10.7831143 11.29849385 11.4957793
CV residual -0.2620702 -0.18599 0.1018039 -0.3349932 0.07386553 0.7915035
[,59] [,60] [,61] [,62] [,63] [,64]
Predicted 10.9433762 10.7476144 10.7120793 10.6954745 10.9224477 10.8180922
cvpred 10.9382635 10.7377191 10.7013050 10.6869741 10.9130432 10.8078966
LNMEDHVAL 10.5213722 10.5584135 10.2715969 10.4012279 10.7099634 10.4252531
CV residual -0.4168912 -0.1793056 -0.4297081 -0.2857461 -0.2030797 -0.3826435
[,65] [,66] [,67] [,68] [,69] [,70]
Predicted 10.6456847 10.7364786 10.71572623 10.5422418 9.149338 10.8418547
cvpred 10.6305687 10.7279215 10.70435718 10.5282822 9.109382 10.8306961
LNMEDHVAL 10.2784935 10.4544950 10.63585545 10.2921455 10.532096 11.5768388
CV residual -0.3520753 -0.2734266 -0.06850173 -0.2361366 1.422714 0.7461427
[,71] [,72] [,73] [,74] [,75] [,76]
Predicted 11.0625696 10.9502865 10.9810920 11.1512706 10.8309260 10.7936113
cvpred 11.0548947 10.9443663 10.9759668 11.1463452 10.8219486 10.7835339
LNMEDHVAL 11.4988265 10.7621492 10.5661755 10.5267486 10.5713169 10.7232674
CV residual 0.4439319 -0.1822171 -0.4097912 -0.6195965 -0.2506317 -0.0602665
[,77] [,78] [,79] [,80] [,81] [,82]
Predicted 10.94890935 10.75821068 10.7742160 10.5539510 11.27121 10.2973138
cvpred 10.93882693 10.74496266 10.7621110 10.5373122 11.27327 10.2764148
LNMEDHVAL 10.98019501 10.66895539 10.6501755 10.1226231 11.03166 10.9835964
CV residual 0.04136807 -0.07600726 -0.1119355 -0.4146892 -0.24161 0.7071815
[,83] [,84] [,85] [,86] [,87] [,88]
Predicted 10.8646133 10.854536 10.8999607 10.836817 11.197957 10.6877181
cvpred 10.8531315 10.844208 10.8910285 10.826401 11.194475 10.6750937
LNMEDHVAL 11.0397167 12.178701 11.4230008 12.154779 12.323856 11.3862278
CV residual 0.1865852 1.334493 0.5319723 1.328379 1.129381 0.7111342
[,89] [,90] [,91] [,92] [,93] [,94]
Predicted 10.882550 10.829329 10.493354937 10.6363020 10.6804949 11.15614028
cvpred 10.873773 10.820721 10.475710304 10.6273899 10.6755606 11.14949790
LNMEDHVAL 12.014912 10.207289 10.474467099 10.4193007 10.1886665 11.17043516
CV residual 1.141139 -0.613432 -0.001243205 -0.2080892 -0.4868941 0.02093726
[,95] [,96] [,97] [,98] [,99] [,100]
Predicted 11.0232918 10.8492809 10.783678 10.8792695 10.8016058 10.9892905
cvpred 11.0144441 10.8375447 10.777632 10.8694920 10.7940345 10.9852314
LNMEDHVAL 11.1287325 11.0300392 10.184900 10.5078035 10.6919449 10.5105320
CV residual 0.1142884 0.1924945 -0.592732 -0.3616885 -0.1020896 -0.4746994
[,101] [,102] [,103] [,104] [,105] [,106]
Predicted 10.9903680 10.0797660 10.971776 10.4436240 10.3004419 10.543243
cvpred 10.9827285 10.0552558 10.968732 10.4302304 10.2856075 10.530051
LNMEDHVAL 10.2506171 10.3640720 9.615805 10.2363820 10.5479696 10.094108
CV residual -0.7321114 0.3088161 -1.352927 -0.1938484 0.2623621 -0.435943
[,107] [,108] [,109] [,110] [,111] [,112]
Predicted 10.61682 10.5659122 10.6872640 10.50440632 10.2743629 10.65472071
cvpred 10.60312 10.5513712 10.6763883 10.48906463 10.2530830 10.64138542
LNMEDHVAL 10.25414 10.2989023 9.9987977 10.40728856 10.0647557 10.60905725
CV residual -0.34898 -0.2524689 -0.6775906 -0.08177606 -0.1883273 -0.03232816
[,113] [,114] [,115] [,116] [,117] [,118]
Predicted 10.9021886 10.9604007 10.97726706 10.8282208 10.9402343 10.8938352
cvpred 10.8913306 10.9505090 10.97326888 10.8184335 10.9368348 10.8833884
LNMEDHVAL 10.3089527 10.8356516 11.03165864 10.9664727 11.6851967 11.0461167
CV residual -0.5823779 -0.1148574 0.05838976 0.1480391 0.7483619 0.1627284
[,119] [,120] [,121] [,122] [,123] [,124]
Predicted 10.9652027 10.9406908 10.6931028 10.9623919 10.3597705 10.8983222
cvpred 10.9557801 10.9304720 10.6798529 10.9531346 10.3417801 10.8874000
LNMEDHVAL 11.2009507 11.0821425 11.2580332 11.7440372 11.2252434 11.8313792
CV residual 0.2451706 0.1516706 0.5781803 0.7909026 0.8834633 0.9439792
[,125] [,126] [,127] [,128] [,129] [,130]
Predicted 10.997226 10.83959 10.84465034 10.9640290 10.8711669 11.1561403
cvpred 10.989221 10.82953 10.84095975 10.9541976 10.8612976 11.1494979
LNMEDHVAL 12.290873 12.29133 10.93489109 11.5327281 11.3361883 11.4435754
CV residual 1.301652 1.46180 0.09393134 0.5785305 0.4748906 0.2940775
[,131] [,132] [,133] [,134] [,135] [,136]
Predicted 10.6158905 10.217292 11.271630 10.519861 10.549567 9.5385760
cvpred 10.6071986 10.205587 11.273716 10.504544 10.532856 9.5162928
LNMEDHVAL 9.8416121 10.413313 10.221941 9.433484 10.876159 9.9664624
CV residual -0.7655865 0.207726 -1.051775 -1.071060 0.343303 0.4501696
[,137] [,138] [,139] [,140] [,141] [,142]
Predicted 9.525374 10.5764586 10.5287141 10.525715 10.8183916 10.9910965
cvpred 9.491660 10.5618950 10.5150328 10.511102 10.8180699 10.9868393
LNMEDHVAL 10.904119 11.2721270 10.7621492 10.628618 10.5610076 10.6759079
CV residual 1.412459 0.7102319 0.2471164 0.117516 -0.2570624 -0.3109314
[,143] [,144] [,145] [,146] [,147] [,148]
Predicted 11.1454722 11.2098095 10.563078 11.2575145 10.667072 10.3196487
cvpred 11.1399340 11.2072234 10.550127 11.2585340 10.659711 10.3031066
LNMEDHVAL 11.0202671 11.0650746 9.417355 11.7424486 10.122623 9.9942419
CV residual -0.1196669 -0.1421488 -1.132772 0.4839146 -0.537088 -0.3088647
[,149] [,150] [,151] [,152] [,153] [,154]
Predicted 10.999925 10.4348345 10.3791910 10.7727181 10.7827868 10.9413366
cvpred 10.996414 10.4186101 10.3596512 10.7641952 10.7726543 10.9334022
LNMEDHVAL 9.692767 10.3545632 10.0982316 10.9903646 10.2255711 10.3889954
CV residual -1.303648 -0.0640469 -0.2614196 0.2261693 -0.5470832 -0.5444069
[,155] [,156] [,157] [,158] [,159] [,160]
Predicted 10.9747458 10.27137949 10.9183946 10.743469 10.682365 10.3573381
cvpred 10.9650922 10.26594906 10.9114567 10.729976 10.670459 10.3412381
LNMEDHVAL 9.9804486 10.31890299 10.0899671 9.375855 9.350102 9.8255260
CV residual -0.9846436 0.05295393 -0.8214895 -1.354121 -1.320357 -0.5157121
[,161] [,162] [,163] [,164] [,165] [,166]
Predicted 10.876047 10.429753 10.9450540 10.8536483 10.8742132 10.7333623
cvpred 10.864756 10.414015 10.9402888 10.8455223 10.8671864 10.7216766
LNMEDHVAL 9.769956 9.287301 10.3189030 10.4282161 10.2327913 10.4429006
CV residual -1.094799 -1.126713 -0.6213858 -0.4173063 -0.6343951 -0.2787759
[,167] [,168] [,169] [,170] [,171] [,172]
Predicted 10.9044853 10.9860847 10.7738922 10.7819579 10.8694193 10.8039965
cvpred 10.8951872 10.9766194 10.7646882 10.7752469 10.8580173 10.7942760
LNMEDHVAL 10.3828225 10.3385115 10.5267486 10.2291877 10.3672216 9.9232902
CV residual -0.5123647 -0.6381079 -0.2379396 -0.5460592 -0.4907958 -0.8709858
[,173] [,174] [,175] [,176] [,177] [,178]
Predicted 10.778742 10.7330358 10.7500138 10.6780206 10.6186902 10.9549510
cvpred 10.774626 10.7300095 10.7450809 10.6795850 10.6053967 10.9497551
LNMEDHVAL 9.581904 9.7699562 10.3951304 10.2182983 10.4602421 10.7831143
CV residual -1.192722 -0.9600533 -0.3499505 -0.4612867 -0.1451546 -0.1666408
[,179] [,180] [,181] [,182] [,183] [,184]
Predicted 10.79704163 10.7666337 10.7980878 10.6627456 11.0213468 10.3170934
cvpred 10.78650324 10.7568298 10.7866442 10.6525815 11.0141751 10.2965228
LNMEDHVAL 10.80770570 11.0120502 10.5374154 10.4995730 10.7298536 10.4995730
CV residual 0.02120247 0.2552204 -0.2492288 -0.1530085 -0.2843215 0.2030502
[,185] [,186] [,187] [,188] [,189] [,190]
Predicted 11.01981584 10.9180325 11.0693307 10.9236318 11.0448743 10.576968
cvpred 11.01091047 10.9131019 11.0640198 10.9195142 11.0408034 10.579209
LNMEDHVAL 10.95430918 10.6873891 10.3513734 10.0212706 10.4222813 9.433484
CV residual -0.05660129 -0.2257128 -0.7126464 -0.8982437 -0.6185221 -1.145725
[,191] [,192] [,193] [,194] [,195] [,196]
Predicted 10.65927745 10.50247597 10.8189744 10.3568859 10.9427026 10.6012888
cvpred 10.64438713 10.49114034 10.8082298 10.3395262 10.9359765 10.5868761
LNMEDHVAL 10.67127828 10.51596683 10.4631033 9.9850675 10.4968144 10.1924188
CV residual 0.02689114 0.02482649 -0.3451265 -0.3544587 -0.4391621 -0.3944572
[,197] [,198] [,199] [,200] [,201] [,202]
Predicted 10.7283456 10.7154229 11.440959 9.842597 11.0802029 11.0225544
cvpred 10.7167180 10.7043612 11.458739 9.814150 11.0764182 11.0173371
LNMEDHVAL 9.9664624 10.4193007 11.793583 10.956056 11.1287325 11.1243175
CV residual -0.7502556 -0.2850605 0.334844 1.141906 0.0523143 0.1069804
[,203] [,204] [,205] [,206] [,207] [,208]
Predicted 11.15614028 11.0412065 10.9757017 10.5212611 11.0693042 11.0150574
cvpred 11.14949790 11.0345568 10.9704979 10.5040797 11.0654601 11.0060731
LNMEDHVAL 11.20504069 11.2721270 11.2606105 11.1533893 11.3337988 11.2064003
CV residual 0.05554278 0.2375701 0.2901126 0.6493096 0.2683387 0.2003272
[,209] [,210] [,211] [,212] [,213] [,214]
Predicted 10.9332449 10.8531774 11.4119602 11.3299246 11.2290655 10.9709833
cvpred 10.9239681 10.8422709 11.4349855 11.3364170 11.2381102 10.9654544
LNMEDHVAL 11.2424282 11.2809934 11.6377944 11.1562505 11.8872438 11.6333716
CV residual 0.3184601 0.4387225 0.2028089 -0.1801664 0.6491336 0.6679172
[,215] [,216] [,217] [,218] [,219] [,220]
Predicted 11.1883474 11.4789783 11.3528059 10.993933 10.9163024 10.6204267
cvpred 11.1968327 11.4967362 11.3724904 10.990393 10.9066645 10.6116476
LNMEDHVAL 11.6118654 11.7035458 11.9349199 11.703546 11.3667430 11.0153451
CV residual 0.4150327 0.2068096 0.5624295 0.713153 0.4600784 0.4036974
[,221] [,222] [,223] [,224] [,225] [,226]
Predicted 10.9750811 10.7486702 10.64862365 10.3979231 10.8656625 10.6274249
cvpred 10.9687626 10.7388754 10.63817553 10.3826952 10.8598204 10.6154937
LNMEDHVAL 11.3725133 10.9920495 10.61643736 10.4370527 10.5453414 10.3920676
CV residual 0.4037507 0.2531741 -0.02173817 0.0543575 -0.3144789 -0.2234261
[,227] [,228] [,229] [,230] [,231] [,232]
Predicted 11.156140 11.0790260 10.6668193 10.7621565 11.2261976 11.1508664
cvpred 11.149498 11.0722785 10.6564787 10.7489739 11.2262849 11.1481796
LNMEDHVAL 11.434964 11.5346870 10.7121931 10.9886768 11.4957793 11.3337988
CV residual 0.285466 0.4624085 0.0557144 0.2397029 0.2694944 0.1856192
[,233] [,234] [,235] [,236] [,237] [,238]
Predicted 11.1973912 11.0960839 11.0376339 11.0370218 11.0206506 11.21300914
cvpred 11.1938666 11.0884446 11.0301974 11.0296975 11.0132134 11.21066493
LNMEDHVAL 11.0775165 11.2131708 11.1619485 11.1732481 11.1272630 11.20367921
CV residual -0.1163501 0.1247262 0.1317512 0.1435506 0.1140495 -0.00698572
[,239] [,240] [,241] [,242] [,243] [,244]
Predicted 10.8180048 10.9919201 11.13100671 10.88080903 10.9629688 11.0095210
cvpred 10.8068150 10.9906152 11.13026592 10.86959615 10.9550999 11.0086782
LNMEDHVAL 11.0037651 11.4647851 11.14475614 10.79548559 10.8257604 10.8336812
CV residual 0.1969501 0.4741699 0.01449022 -0.07411055 -0.1293395 -0.1749971
[,245] [,246] [,247] [,248] [,249]
Predicted 10.82803585 10.9827189 10.94132839 11.00867595 10.51069351
cvpred 10.82546469 10.9789748 10.93540948 11.00062509 10.49866181
LNMEDHVAL 10.90595598 10.8780472 10.98867682 11.02190247 10.43998092
CV residual 0.08049129 -0.1009276 0.05326734 0.02127738 -0.05868089
[,250] [,251] [,252] [,253] [,254] [,255]
Predicted 10.9149597 10.9269126 10.9701238 9.382720 10.4045793 10.3865905
cvpred 10.9055479 10.9174456 10.9689680 9.348156 10.3866627 10.3671735
LNMEDHVAL 10.6964801 10.3703613 9.9711462 10.976782 10.6828124 10.7450547
CV residual -0.2090678 -0.5470843 -0.9978218 1.628626 0.2961497 0.3778812
[,256] [,257] [,258] [,259] [,260] [,261]
Predicted 10.9382928 11.0581886 11.141387 11.0679345 10.9649409 11.0405162
cvpred 10.9299777 11.0550217 11.143314 11.0707558 10.9629803 11.0361916
LNMEDHVAL 10.7789563 10.7472076 10.879932 10.6261935 10.5479696 10.6065851
CV residual -0.1510214 -0.3078141 -0.263382 -0.4445623 -0.4150108 -0.4296066
[,262] [,263] [,264] [,265] [,266] [,267]
Predicted 10.8686688 11.0482131 10.9895395 10.9728764 11.0968284 11.2637533
cvpred 10.8662231 11.0420307 10.9815972 10.9698399 11.0902087 11.2652443
LNMEDHVAL 10.3089527 10.7166375 10.5815211 10.6873891 10.9647441 10.9987609
CV residual -0.5572704 -0.3253932 -0.4000761 -0.2824508 -0.1254646 -0.2664834
[,268] [,269] [,270] [,271] [,272] [,273]
Predicted 11.1568961 11.1298166 10.9873129 10.8741818 10.5569840 10.7695292
cvpred 11.1577999 11.1307861 10.9799896 10.8649516 10.5517516 10.7668843
LNMEDHVAL 10.9348911 10.7557730 11.2733984 10.6213273 10.6016223 10.5294260
CV residual -0.2229088 -0.3750131 0.2934088 -0.2436242 0.0498707 -0.2374583
[,274] [,275] [,276] [,277] [,278] [,279]
Predicted 10.93325833 11.2194988 11.1049915 10.9751029 10.9625378 10.7639453
cvpred 10.92784442 11.2176451 11.1002739 10.9689974 10.9564142 10.7525087
LNMEDHVAL 10.97848998 10.5320962 10.8277465 10.6549036 10.6041067 10.9187182
CV residual 0.05064556 -0.6855489 -0.2725274 -0.3140937 -0.3523075 0.1662095
[,280] [,281] [,282] [,283] [,284]
Predicted 10.7094900 10.97955975 10.85925488 11.0514630 11.05875055
cvpred 10.6954333 10.97258326 10.84768420 11.0451879 11.05753709
LNMEDHVAL 10.8666619 10.95080655 10.80567936 10.8818137 10.97507117
CV residual 0.1712286 -0.02177671 -0.04200484 -0.1633743 -0.08246593
[,285] [,286] [,287] [,288] [,289] [,290]
Predicted 11.1769313 11.1561403 10.9565840 11.0341892 11.1100909 11.2340812
cvpred 11.1813574 11.1494979 10.9564909 11.0280558 11.1119028 11.2333296
LNMEDHVAL 11.3132543 11.1331281 11.3169106 11.2872788 11.3290026 11.3527567
CV residual 0.1318968 -0.0163698 0.3604197 0.2592229 0.2170998 0.1194271
[,291] [,292] [,293] [,294] [,295]
Predicted 11.03165316 11.1678900 11.1054924 10.8483583 11.15614028
cvpred 11.02294429 11.1696549 11.1042842 10.8377982 11.14949790
LNMEDHVAL 11.11542853 11.5297826 11.3445068 10.9223349 11.19684392
CV residual 0.09248423 0.3601277 0.2402226 0.0845367 0.04734602
[,296] [,297] [,298] [,299] [,300] [,301]
Predicted 11.02635103 10.99870997 11.0172604 11.0961029 11.156140 11.0933156
cvpred 11.01943928 10.99437481 11.0083127 11.0884639 11.149498 11.0875812
LNMEDHVAL 10.99541085 11.03327546 11.2198958 11.1995836 10.969921 11.2708539
CV residual -0.02402843 0.03890065 0.2115831 0.1111197 -0.179577 0.1832727
[,302] [,303] [,304] [,305] [,306]
Predicted 11.07404405 11.0452459 11.02077010 11.00675637 10.985752804
cvpred 11.06603887 11.0367627 11.01439515 10.99763422 10.977060002
LNMEDHVAL 11.15482093 10.8704714 11.07596969 10.95954023 10.969920943
CV residual 0.08878206 -0.1662913 0.06157454 -0.03809399 -0.007139059
[,307] [,308] [,309] [,310] [,311] [,312]
Predicted 10.9343995 10.9770935 10.88668157 11.0186285 11.28101802 10.550329
cvpred 10.9324689 10.9689978 10.88111164 11.0147427 11.28381396 10.535022
LNMEDHVAL 10.8257604 10.8473935 10.92773543 10.7995756 11.23980354 11.036501
CV residual -0.1067085 -0.1216043 0.04662378 -0.2151671 -0.04401042 0.501479
[,313] [,314] [,315] [,316] [,317]
Predicted 10.7182023 10.8611754 11.01966149 10.966054404 11.04469012
cvpred 10.7155089 10.8496366 11.01302114 10.960023429 11.03988340
LNMEDHVAL 10.8799322 10.7684850 11.02679245 10.956055903 10.99373159
CV residual 0.1644233 -0.0811516 0.01377131 -0.003967527 -0.04615181
[,318] [,319] [,320] [,321] [,322] [,323]
Predicted 10.90969075 11.0721045 10.9426063 11.1539744 10.8594090 11.0520006
cvpred 10.90680163 11.0667117 10.9359579 11.1527739 10.8491375 11.0455277
LNMEDHVAL 10.82972862 10.8761586 11.0759697 11.1228415 11.3217650 11.4175153
CV residual -0.07707301 -0.1905531 0.1400118 -0.0299324 0.4726274 0.3719876
[,324] [,325] [,326] [,327] [,328] [,329]
Predicted 10.9998457 11.0988240 11.0726549 11.042839 11.1102991 11.1327943
cvpred 10.9906088 11.0945136 11.0712838 11.035024 11.1155917 11.1294795
LNMEDHVAL 11.3361883 11.4240943 11.3621026 11.327800 11.6835118 11.5366420
CV residual 0.3455794 0.3295806 0.2908188 0.292776 0.5679201 0.4071625
[,330] [,331] [,332] [,333] [,334] [,335]
Predicted 11.1131815 11.47045137 12.02465542 11.0683147 11.097878 11.1008899
cvpred 11.1087267 11.49157930 12.08491511 11.0624334 11.094067 11.0933304
LNMEDHVAL 11.6369114 11.50791292 12.04414178 11.4584693 11.464785 11.2935249
CV residual 0.5281847 0.01633362 -0.04077333 0.3960359 0.370718 0.2001945
[,336] [,337] [,338] [,339] [,340] [,341]
Predicted 11.0015996 11.3073279 11.0876618 11.1160160 11.0278189 11.3933175
cvpred 10.9932303 11.3138339 11.0835134 11.1122209 11.0195431 11.4068626
LNMEDHVAL 11.3265959 11.5287988 11.4595247 11.6045927 11.5248540 11.6613455
CV residual 0.3333656 0.2149649 0.3760113 0.4923718 0.5053109 0.2544828
[,342] [,343] [,344]
Predicted 11.1114289 11.18232 11.0896621
cvpred 11.1040443 11.18019 11.0819162
LNMEDHVAL 11.3736634 11.49170 11.4637352
CV residual 0.2696191 0.31151 0.3818191
Sum of squares = 101.16 Mean square = 0.29 n = 344
Overall (Sum over all 344 folds)
ms
0.2782169 [1] 0.5274627
fold 1
Observations in test set: 344
[,1] [,2] [,3] [,4] [,5] [,6]
Predicted 11.557499 11.6828812 10.9620047 11.34662 11.0407941 10.951747
cvpred 11.556902 11.6823824 10.9651308 11.35033 11.0438758 10.951971
LNMEDHVAL 12.672319 12.1291916 11.6055046 12.38506 11.9984333 13.004930
CV residual 1.115417 0.4468092 0.6403739 1.03473 0.9545575 2.052959
[,7] [,8] [,9] [,10] [,11] [,12]
Predicted 10.9365417 11.4224071 11.7159745 11.1322431 11.2878702 11.0014339
cvpred 10.9394338 11.4240965 11.7170639 11.1326079 11.2919880 11.0037815
LNMEDHVAL 11.4008760 12.3238557 11.9183906 11.9652742 11.6784399 11.4031106
CV residual 0.4614421 0.8997592 0.2013267 0.8326663 0.3864519 0.3993291
[,13] [,14] [,15] [,16] [,17] [,18]
Predicted 10.278641 10.333066 10.8045985 11.0355314 10.2723058 10.7137237
cvpred 10.277580 10.335727 10.8079252 11.0364185 10.2735066 10.7153836
LNMEDHVAL 12.323856 10.134599 10.6310362 10.7600283 11.0020998 11.2424282
CV residual 2.046276 -0.201128 -0.1768891 -0.2763902 0.7285932 0.5270446
[,19] [,20] [,21] [,22] [,23] [,24]
Predicted 10.4162208 10.8514124 10.6906174 10.6914759 10.6469488 10.5022005
cvpred 10.4210502 10.8551366 10.6956995 10.6976391 10.6520612 10.5083807
LNMEDHVAL 10.6213273 11.0728689 10.8930287 10.8742665 10.4659564 10.6286178
CV residual 0.2002772 0.2177323 0.1973292 0.1766274 -0.1861048 0.1202371
[,25] [,26] [,27] [,28] [,29] [,30]
Predicted 10.6554315 10.4889888 10.32945158 10.9281180 10.609053 10.3449596
cvpred 10.6549749 10.4934901 10.33331050 10.9308298 10.617973 10.3452670
LNMEDHVAL 10.5400644 10.3189030 10.42821608 10.0690020 9.268609 9.6927665
CV residual -0.1149105 -0.1745871 0.09490558 -0.8618279 -1.349364 -0.6525005
[,31] [,32] [,33] [,34] [,35] [,36]
Predicted 10.8433109 10.8004300 10.802652 10.95604859 11.10165597 10.8509371
cvpred 10.8451230 10.8036235 10.807940 10.95980398 11.10521897 10.8560628
LNMEDHVAL 9.8934372 10.5023241 10.635855 10.99204951 11.19958365 11.0898054
CV residual -0.9516858 -0.3012994 -0.172085 0.03224552 0.09436467 0.2337426
[,37] [,38] [,39] [,40] [,41] [,42]
Predicted 10.7973676 10.5053517 10.79074 10.9131281 10.9032730 10.8399546
cvpred 10.7999508 10.5045736 10.79469 10.9169181 10.9074717 10.8433052
LNMEDHVAL 11.0697585 9.7699562 10.60162 10.7254676 10.6942151 10.7298536
CV residual 0.2698077 -0.7346175 -0.19307 -0.1914505 -0.2132567 -0.1134516
[,43] [,44] [,45] [,46] [,47] [,48]
Predicted 10.59868255 10.6932027 10.8748098 10.751864 10.5061073 10.99170923
cvpred 10.60238346 10.6969971 10.8805356 10.752874 10.5032046 10.99678074
LNMEDHVAL 10.51053203 10.4912742 10.6188853 10.271597 10.2435249 10.93310697
CV residual -0.09185143 -0.2057229 -0.2616503 -0.481277 -0.2596797 -0.06367377
[,49] [,50] [,51] [,52] [,53] [,54]
Predicted 10.8220682 10.8563654 10.2861084 10.7180893 10.71156757 10.4735165
cvpred 10.8247008 10.8635357 10.2875609 10.7201323 10.71416918 10.4774109
LNMEDHVAL 10.5891065 10.5078035 10.4659564 10.3254820 10.64304111 10.6041067
CV residual -0.2355944 -0.3557322 0.1783956 -0.3946503 -0.07112808 0.1266959
[,55] [,56] [,57] [,58] [,59] [,60]
Predicted 10.80225196 10.312243 10.31701013 10.5519285 10.7611344 10.8929092
cvpred 10.80601322 10.316964 10.31920776 10.5569880 10.7615030 10.8940504
LNMEDHVAL 10.81777628 10.465956 10.30226367 10.3513734 11.2910311 11.5655179
CV residual 0.01176306 0.148992 -0.01694409 -0.2056146 0.5295281 0.6714675
[,61] [,62] [,63] [,64] [,65]
Predicted 10.6569235 10.5442831302 10.8832579 10.8900225 10.9543736
cvpred 10.6573656 10.5496716530 10.8857991 10.8943275 10.9585701
LNMEDHVAL 11.0300392 10.5505907946 10.4912742 10.4042628 11.0958937
CV residual 0.3726736 0.0009191416 -0.3945249 -0.4900647 0.1373236
[,66] [,67] [,68] [,69] [,70]
Predicted 10.87654032 10.5227724 10.54317362260 10.7638369 10.7451133
cvpred 10.88107578 10.5262539 10.54541723288 10.7686236 10.7479114
LNMEDHVAL 10.95954023 10.6712783 10.54534143871 10.4544950 10.6016223
CV residual 0.07846445 0.1450244 -0.00007579417 -0.3141287 -0.1462891
[,71] [,72] [,73] [,74] [,75] [,76]
Predicted 10.7899327 10.9143106 10.4641391 10.5334990 10.3151391 10.663214
cvpred 10.7932197 10.9175909 10.4701361 10.5378566 10.3152490 10.667692
LNMEDHVAL 10.4341158 10.5610076 11.1562505 10.9150885 10.4912742 10.292146
CV residual -0.3591039 -0.3565834 0.6861144 0.3772319 0.1760252 -0.375547
[,77] [,78] [,79] [,80] [,81] [,82]
Predicted 10.544543 10.4064869 10.5912646 10.50211258 10.6950362 11.0137682
cvpred 10.547845 10.4091487 10.5938722 10.50562419 10.6970961 11.0172379
LNMEDHVAL 10.134599 10.2327913 10.4222813 10.52137225 10.8874369 11.1243175
CV residual -0.413246 -0.1763574 -0.1715909 0.01574806 0.1903408 0.1070796
[,83] [,84] [,85] [,86] [,87] [,88]
Predicted 10.73132644 10.6386786 10.7213994 10.4896295 10.2682086 10.3991013
cvpred 10.73536020 10.6393349 10.7223262 10.4916578 10.2720822 10.4017646
LNMEDHVAL 10.71885237 10.4370527 10.2750511 10.1924188 10.0816337 10.5347593
CV residual -0.01650784 -0.2022822 -0.4472751 -0.2992389 -0.1904485 0.1329947
[,89] [,90] [,91] [,92] [,93]
Predicted 10.45965531 11.02695643 10.49000975 10.3428578 10.4363214
cvpred 10.46125397 11.03217131 10.49240363 10.3482372 10.4378702
LNMEDHVAL 10.43117029 11.05247605 10.43411580 10.5400644 10.2327913
CV residual -0.03008367 0.02030474 -0.05828783 0.1918272 -0.2050789
[,94] [,95] [,96] [,97] [,98] [,99]
Predicted 10.8633772 10.6856503 10.863091 11.26117 11.0144636 10.8333874
cvpred 10.8663017 10.6912036 10.864700 11.26548 11.0175974 10.8338194
LNMEDHVAL 10.3672216 10.5738777 9.846917 10.78519 11.3169106 11.2797316
CV residual -0.4990801 -0.1173258 -1.017782 -0.48029 0.2993132 0.4459122
[,100] [,101] [,102] [,103] [,104] [,105]
Predicted 11.5753825 11.1123774 10.654186 11.4668888 10.86438015 11.1624145
cvpred 11.5753538 11.1143808 10.660234 11.4681909 10.86809656 11.1654001
LNMEDHVAL 11.1490820 10.9852927 11.895463 11.5740206 10.96301245 10.8855660
CV residual -0.4262718 -0.1290881 1.235229 0.1058297 0.09491589 -0.2798341
[,106] [,107] [,108] [,109] [,110] [,111]
Predicted 11.04553506 11.18341623 11.0695908 11.0246187 10.5656728 9.8173579
cvpred 11.04966783 11.18520828 11.0720669 11.0283160 10.5663055 9.8098450
LNMEDHVAL 10.99373159 11.22123537 10.9059560 11.9524699 11.2567421 10.7144178
CV residual -0.05593624 0.03602709 -0.1661109 0.9241539 0.6904365 0.9045728
[,112] [,113] [,114] [,115] [,116]
Predicted 11.4910807 11.20552385 10.9569907 10.8194527 10.8684668
cvpred 11.4937610 11.21022424 10.9573989 10.8221241 10.8711947
LNMEDHVAL 11.6307085 11.22524339 11.3997568 10.6188853 11.2252434
CV residual 0.1369475 0.01501915 0.4423579 -0.2032387 0.3540487
[,117] [,118] [,119] [,120] [,121]
Predicted 11.761902073 11.0107356 11.406434039 10.6020608 10.8926052
cvpred 11.762666536 11.0084957 11.407386079 10.6029814 10.8939831
LNMEDHVAL 11.760566488 11.7943379 11.405340254 10.3254820 10.7472076
CV residual -0.002100049 0.7858422 -0.002045825 -0.2774994 -0.1467755
[,122] [,123] [,124] [,125] [,126]
Predicted 10.0046380 10.478981576 10.65369200 10.3597697 10.23138684
cvpred 10.0045940 10.477489196 10.66130620 10.3568940 10.23502748
LNMEDHVAL 9.6023825 10.474467099 10.71441777 10.9595402 10.27505111
CV residual -0.4022115 -0.003022097 0.05311157 0.6026462 0.04002363
[,127] [,128] [,129] [,130] [,131] [,132]
Predicted 10.5444102 10.6846286 10.7581065 10.1224567 9.1979316 10.4561092
cvpred 10.5515796 10.6858467 10.7639004 10.1218693 9.1880815 10.4599346
LNMEDHVAL 11.0284171 9.9330464 10.2219413 10.3889954 9.7699562 10.0774409
CV residual 0.4768375 -0.7528004 -0.5419592 0.2671261 0.5818747 -0.3824937
[,133] [,134] [,135] [,136] [,137] [,138]
Predicted 10.6239886 10.7466431 10.6919560 10.7331943 10.89643001 10.2802458
cvpred 10.6256950 10.7501203 10.6943842 10.7350652 10.89846962 10.2806163
LNMEDHVAL 10.1105017 10.9886768 10.5661755 10.5159668 10.82774645 10.1185989
CV residual -0.5151932 0.2385565 -0.1282087 -0.2190984 -0.07072317 -0.1620174
[,139] [,140] [,141] [,142] [,143] [,144]
Predicted 10.3391179 10.3989801 10.3968289 10.2894452 10.242924 10.9441583
cvpred 10.3408074 10.4032002 10.4005966 10.2927167 10.244458 10.9406841
LNMEDHVAL 9.8201059 11.0508900 10.1185989 10.0475879 10.618885 10.3889954
CV residual -0.5207014 0.6476898 -0.2819976 -0.2451288 0.374427 -0.5516888
[,145] [,146] [,147] [,148] [,149] [,150]
Predicted 10.3748412 10.7238105 10.3103560 10.3637927 10.1160378 10.3945992
cvpred 10.3800077 10.7279482 10.3121984 10.3633908 10.1183090 10.3991738
LNMEDHVAL 10.0982316 10.2576594 9.8984750 9.5030100 9.3842937 9.8036672
CV residual -0.2817761 -0.4702888 -0.4137234 -0.8603808 -0.7340154 -0.5955065
[,151] [,152] [,153] [,154] [,155] [,156]
Predicted 10.2793593 11.1379570 10.4295699 10.6476984 10.379324 10.3059957
cvpred 10.2802869 11.1425950 10.4336981 10.6505357 10.380512 10.3101695
LNMEDHVAL 9.6091165 10.3513734 10.1145585 10.0774409 9.961756 10.0212706
CV residual -0.6711704 -0.7912216 -0.3191395 -0.5730948 -0.418755 -0.2888989
[,157] [,158] [,159] [,160] [,161] [,162]
Predicted 10.6075261 10.4386240 10.1354421 10.49037475 10.2002061 10.3568588
cvpred 10.6126259 10.4439005 10.1369321 10.49611305 10.2024369 10.3601286
LNMEDHVAL 9.8146563 9.7291342 9.7526647 10.39818379 9.8036672 9.8416121
CV residual -0.7979696 -0.7147664 -0.3842674 -0.09792925 -0.3987697 -0.5185164
[,163] [,164] [,165] [,166] [,167]
Predicted 10.261490708 10.39036733 10.3826586 10.7610009 10.21423458
cvpred 10.265015030 10.39455289 10.3855532 10.7655691 10.21382912
LNMEDHVAL 10.271596874 10.34496310 10.0816337 10.5991316 10.22918769
CV residual 0.006581844 -0.04958979 -0.3039194 -0.1664375 0.01535857
[,168] [,169] [,170] [,171] [,172] [,173]
Predicted 10.6804076 11.0477850 11.0084180 11.0701132 11.0938349 10.95506340
cvpred 10.6817534 11.0526200 11.0115467 11.0757715 11.0965900 10.96153558
LNMEDHVAL 10.5023241 11.3504065 10.7385682 10.8297286 10.9595402 11.05721914
CV residual -0.1794293 0.2977866 -0.2729785 -0.2460428 -0.1370498 0.09568356
[,174] [,175] [,176] [,177] [,178] [,179]
Predicted 10.9040222 10.9197383 10.55282813 10.7908916 10.50825449 11.0626405
cvpred 10.9092343 10.9213444 10.55429584 10.7964876 10.51012970 11.0683517
LNMEDHVAL 11.0153451 10.8157703 10.46595641 10.5815211 10.42228135 10.7493558
CV residual 0.1061108 -0.1055742 -0.08833943 -0.2149665 -0.08784835 -0.3189958
[,180] [,181] [,182] [,183] [,184] [,185]
Predicted 11.1140106 10.9403301 10.5424828 10.6548130 10.18131350 10.5182887
cvpred 11.1181638 10.9432687 10.5469309 10.6605701 10.18320431 10.5223673
LNMEDHVAL 10.8551454 10.7747809 10.3577428 10.4631033 10.26116200 10.2887500
CV residual -0.2630183 -0.1684878 -0.1891881 -0.1974667 0.07795769 -0.2336173
[,186] [,187] [,188] [,189] [,190] [,191]
Predicted 10.6336545 10.6712565 10.505536 10.5741014 10.3495476 10.5445377
cvpred 10.6424004 10.6742086 10.509669 10.5772220 10.3531326 10.5474292
LNMEDHVAL 10.7557730 10.3254820 10.395130 10.4716382 10.4801009 10.0212706
CV residual 0.1133725 -0.3487266 -0.114539 -0.1055838 0.1269683 -0.5261586
[,192] [,193] [,194] [,195] [,196] [,197]
Predicted 10.6096276 10.539338 10.3640718 10.3734531 10.6129402 10.3339230
cvpred 10.6149734 10.541072 10.3635665 10.3779519 10.6136760 10.3331504
LNMEDHVAL 10.2819240 10.385914 10.1503476 10.2681307 10.0732303 10.1961572
CV residual -0.3330494 -0.155158 -0.2132189 -0.1098213 -0.5404456 -0.1369933
[,198] [,199] [,200] [,201] [,202] [,203]
Predicted 10.8967514 10.5514200 11.3917483 11.11227046 11.5541714 11.1129767
cvpred 10.9036361 10.5514258 11.3939344 11.11470758 11.5557493 11.1141421
LNMEDHVAL 10.4222813 10.3287553 11.2398035 11.20095070 11.3839551 11.0681996
CV residual -0.4813547 -0.2226705 -0.1541309 0.08624312 -0.1717942 -0.0459425
[,204] [,205] [,206] [,207] [,208]
Predicted 11.1084609 11.1870212 11.25561589 11.0926455 11.27021608
cvpred 11.1121648 11.1891979 11.25862587 11.0966135 11.27102883
LNMEDHVAL 11.3034382 11.3702092 11.33976185 11.2502612 11.31080928
CV residual 0.1912734 0.1810113 0.08113597 0.1536476 0.03978045
[,209] [,210] [,211] [,212] [,213]
Predicted 11.71336721 11.51020974 11.1951780 11.2475451 11.87228315
cvpred 11.71314333 11.51206785 11.1991831 11.2509576 11.87171942
LNMEDHVAL 11.76134682 11.60185167 11.7566556 11.7134143 11.95825211
CV residual 0.04820349 0.08978383 0.5574725 0.4624568 0.08653269
[,214] [,215] [,216] [,217] [,218] [,219]
Predicted 12.0504500 14.5206224 11.637756 11.188541 12.3719324 10.9384895
cvpred 12.0476575 14.4997140 11.637459 11.192258 12.3683814 10.9422661
LNMEDHVAL 12.3238557 13.6456708 11.782953 11.456355 12.5974388 11.1243175
CV residual 0.2761982 -0.8540433 0.145494 0.264097 0.2290574 0.1820514
[,220] [,221] [,222] [,223] [,224] [,225]
Predicted 10.6913395 10.48674915 10.428942 10.6524773 11.2786763 10.6009308
cvpred 10.6985897 10.49202568 10.435074 10.6538117 11.2828592 10.6042388
LNMEDHVAL 11.3132543 10.45160896 11.448920 11.0806029 11.1418618 10.7472076
CV residual 0.6146645 -0.04041672 1.013846 0.4267912 -0.1409974 0.1429688
[,226] [,227] [,228] [,229] [,230] [,231]
Predicted 10.5262849 10.5356248 10.7956137 10.9307111 11.3299982 11.0853036
cvpred 10.5285621 10.5385565 10.7973470 10.9313896 11.3303393 11.0863023
LNMEDHVAL 10.6828124 10.1811193 10.6572594 10.5427064 11.4845260 12.0161221
CV residual 0.1542504 -0.3574372 -0.1400876 -0.3886832 0.1541867 0.9298197
[,232] [,233] [,234] [,235] [,236] [,237]
Predicted 11.5419341 11.10665788 11.096292 11.3203966 11.2450702 10.8840743
cvpred 11.5426974 11.11205767 11.098697 11.3226696 11.2494909 10.8884472
LNMEDHVAL 11.8159886 11.09892403 11.061940 11.0219025 11.4360444 11.0477104
CV residual 0.2732913 -0.01313364 -0.036757 -0.3007671 0.1865536 0.1592631
[,238] [,239] [,240] [,241] [,242] [,243]
Predicted 11.229873 11.3130657 11.0902666 11.03274014 11.0022924 11.0950081
cvpred 11.234401 11.3156289 11.0947078 11.03522091 11.0084304 11.1004903
LNMEDHVAL 10.811746 11.1094584 10.9472916 10.96127785 10.6642934 10.6572594
CV residual -0.422655 -0.2061706 -0.1474162 -0.07394306 -0.3441371 -0.4432309
[,244] [,245] [,246] [,247] [,248] [,249]
Predicted 10.954375020 10.8076445 11.271932 11.2298038 11.0565814 11.007472
cvpred 10.957129082 10.8111770 11.271129 11.2309053 11.0605450 11.011806
LNMEDHVAL 10.961277847 11.1927202 11.461632 11.4917018 11.6622072 11.790557
CV residual 0.004148765 0.3815432 0.190503 0.2607966 0.6016621 0.778751
[,250] [,251] [,252] [,253] [,254] [,255]
Predicted 10.8420140 10.7351513 10.9666815 11.2229743 10.6291206 10.6044823
cvpred 10.8471885 10.7385626 10.9721571 11.2258314 10.6378985 10.6082956
LNMEDHVAL 11.0681996 10.9022795 10.7363967 11.0928542 11.0852147 10.8855660
CV residual 0.2210111 0.1637169 -0.2357604 -0.1329772 0.4473162 0.2772704
[,256] [,257] [,258] [,259] [,260] [,261]
Predicted 10.5369954 10.7040131 10.8015432 10.9576551 10.7193964 10.9968910
cvpred 10.5442777 10.7066631 10.8043803 10.9626562 10.7201092 11.0006794
LNMEDHVAL 10.7934343 10.9259385 10.4602421 10.5713169 10.5584135 10.6805162
CV residual 0.2491566 0.2192754 -0.3441382 -0.3913393 -0.1616956 -0.3201632
[,262] [,263] [,264] [,265] [,266]
Predicted 10.4671951 10.98070869 11.1459253 10.68997908 10.9994486
cvpred 10.4674752 10.98532217 11.1484617 10.69354830 11.0017227
LNMEDHVAL 10.9384498 10.91326863 10.5584135 10.75363848 10.8097279
CV residual 0.4709746 -0.07205354 -0.5900482 0.06009018 -0.1919948
[,267] [,268] [,269] [,270] [,271] [,272]
Predicted 10.73476712 10.6660510 11.160426 10.9927518 10.54668284 10.66038709
cvpred 10.73888065 10.6721227 11.164264 10.9958370 10.55317573 10.66523572
LNMEDHVAL 10.71663753 10.2146420 11.020267 10.8551454 10.50780352 10.61643736
CV residual -0.02224312 -0.4574807 -0.143997 -0.1406916 -0.04537221 -0.04879836
[,273] [,274] [,275] [,276] [,277] [,278]
Predicted 10.75325927 10.8118201 10.38385258 10.8894850 10.648102 10.6075336
cvpred 10.75949656 10.8180802 10.38551915 10.8905950 10.653647 10.6083305
LNMEDHVAL 10.71441777 10.4631033 10.41331268 10.6942151 10.547970 10.7684850
CV residual -0.04507879 -0.3549768 0.02779352 -0.1963799 -0.105677 0.1601544
[,279] [,280] [,281] [,282] [,283] [,284]
Predicted 11.33738713 11.755105 10.83887613 11.0808177 11.1017524 10.989528
cvpred 11.34115469 11.755191 10.84264823 11.0828594 11.1056169 10.994317
LNMEDHVAL 11.39639165 11.242428 10.81376021 10.8855660 10.7789563 10.872371
CV residual 0.05523696 -0.512763 -0.02888802 -0.1972934 -0.3266606 -0.121946
[,285] [,286] [,287] [,288] [,289] [,290]
Predicted 11.2744572 10.5510596 10.8698959 10.884065 11.0425267 11.3786448
cvpred 11.2786699 10.5527719 10.8756166 10.888799 11.0459633 11.3797834
LNMEDHVAL 11.0603687 10.7810375 10.7621492 11.189962 10.8589990 11.2515607
CV residual -0.2183011 0.2282655 -0.1134674 0.301163 -0.1869643 -0.1282227
[,291] [,292] [,293] [,294] [,295] [,296]
Predicted 11.617913 10.9891690 11.28808009 11.09980067 11.1170602 10.8981913
cvpred 11.618369 10.9928576 11.29219646 11.10272953 11.1198033 10.9006674
LNMEDHVAL 11.480402 11.6307085 11.27593651 11.03327546 10.9455295 11.0635085
CV residual -0.137967 0.6378509 -0.01625995 -0.06945407 -0.1742738 0.1628411
[,297] [,298] [,299] [,300] [,301] [,302]
Predicted 11.06588167 11.1375649 11.2338426 11.0510136 11.0310009 11.2808593
cvpred 11.06981520 11.1413487 11.2366189 11.0539822 11.0336935 11.2850268
LNMEDHVAL 11.11095425 11.0413206 11.0461167 10.9384498 10.9205282 10.8197783
CV residual 0.04113904 -0.1000282 -0.1905021 -0.1155324 -0.1131653 -0.4652485
[,303] [,304] [,305] [,306] [,307] [,308]
Predicted 11.2410914 10.89717 11.3178944 10.9063441 10.9513558 11.1652392
cvpred 11.2451090 10.90027 11.3203202 10.9131609 10.9552986 11.1684801
LNMEDHVAL 11.0493014 10.61644 11.0728689 10.6139834 11.3083583 11.2935249
CV residual -0.1958076 -0.28383 -0.2474512 -0.2991776 0.3530597 0.1250448
[,309] [,310] [,311] [,312] [,313] [,314]
Predicted 10.65578211 11.171525 11.1462393 10.9344031 11.5804169 11.35239545
cvpred 10.65896749 11.174450 11.1496960 10.9378085 11.5824652 11.35605683
LNMEDHVAL 10.69648007 10.992050 10.9543092 11.0836798 11.4175153 11.42300076
CV residual 0.03751258 -0.182401 -0.1953868 0.1458713 -0.1649499 0.06694392
[,315] [,316] [,317] [,318] [,319] [,320]
Predicted 11.62695769 10.9291626 11.36236391 10.9523195 11.0772153 11.3013998
cvpred 11.62772069 10.9342038 11.36468362 10.9571260 11.0812429 11.3037769
LNMEDHVAL 11.70271904 11.3678997 11.28853113 11.4240943 11.5898865 11.4219061
CV residual 0.07499834 0.4336959 -0.07615249 0.4669682 0.5086436 0.1181291
[,321] [,322] [,323] [,324] [,325] [,326]
Predicted 11.24228292 11.1124948 11.2906315 11.262430 11.3231143 10.8919023
cvpred 11.24479252 11.1163114 11.2922079 11.266727 11.3257974 10.8973129
LNMEDHVAL 11.33618829 11.3805363 11.3930152 11.372513 11.4425030 11.4521133
CV residual 0.09139577 0.2642249 0.1008072 0.105786 0.1167056 0.5548004
[,327] [,328] [,329] [,330] [,331] [,332]
Predicted 11.1662476 11.1375724 11.67534371 10.9600525 11.54548879 11.4233229
cvpred 11.1695015 11.1416368 11.67616466 10.9652333 11.54656390 11.4264825
LNMEDHVAL 11.5991032 11.6733422 11.66220717 11.6163842 11.45529635 11.7068462
CV residual 0.4296017 0.5317054 -0.01395749 0.6511509 -0.09126755 0.2803637
[,333] [,334] [,335] [,336] [,337] [,338]
Predicted 11.2505062 12.0168545 11.4601808 11.3398605 11.5705712 12.2393135
cvpred 11.2538789 12.0158154 11.4629175 11.3426837 11.5711799 12.2367006
LNMEDHVAL 11.5199011 11.6342578 11.7775948 11.7051974 11.3850921 11.8182018
CV residual 0.2660222 -0.3815577 0.3146772 0.3625137 -0.1860878 -0.4184988
[,339] [,340] [,341] [,342] [,343]
Predicted 11.7554352 11.33840374 11.7305420 11.42604313 11.50606801
cvpred 11.7551872 11.34146553 11.7315283 11.42880751 11.50864229
LNMEDHVAL 11.4230008 11.40311060 11.4008760 11.36905509 11.46163217
CV residual -0.3321864 0.06164507 -0.3306524 -0.05975242 -0.04701012
[,344]
Predicted 11.61639487
cvpred 11.61818868
LNMEDHVAL 11.62892914
CV residual 0.01074046
Sum of squares = 56.41 Mean square = 0.16 n = 344
fold 2
Observations in test set: 344
[,1] [,2] [,3] [,4] [,5] [,6]
Predicted 10.994421 10.196846 11.00724499 10.743730 12.1007128 10.810337
cvpred 10.991812 10.205461 11.00794062 10.740953 12.1033245 10.809597
LNMEDHVAL 12.323856 13.017003 10.97335737 12.595747 12.6555546 11.956328
CV residual 1.332044 2.811542 -0.03458325 1.854794 0.5522301 1.146731
[,7] [,8] [,9] [,10] [,11] [,12]
Predicted 11.4740999 10.5271675 10.4340655 10.6123812 10.517157 11.2715251
cvpred 11.4741065 10.5293667 10.4426210 10.6172243 10.522985 11.2746370
LNMEDHVAL 12.4634244 10.7995756 10.7144178 10.8874369 11.584315 11.9984333
CV residual 0.9893179 0.2702089 0.2717968 0.2702127 1.061331 0.7237963
[,13] [,14] [,15] [,16] [,17] [,18]
Predicted 10.4020069 11.3625361 11.0617217 10.6082963 10.3537489 10.6393338
cvpred 10.4103416 11.3630173 11.0644314 10.6122782 10.3621649 10.6430938
LNMEDHVAL 10.7684850 12.1388639 11.4446466 10.2989023 10.1385597 10.1464337
CV residual 0.3581434 0.7758466 0.3802152 -0.3133758 -0.2236052 -0.4966601
[,19] [,20] [,21] [,22] [,23] [,24]
Predicted 10.3354714 10.3963103 10.7217663 10.9764663 10.9417925 10.9412484
cvpred 10.3454060 10.4056593 10.7284120 10.9800475 10.9493912 10.9433211
LNMEDHVAL 10.0345158 10.2750511 10.0345158 11.2541547 11.2064003 11.0603687
CV residual -0.3108902 -0.1306082 -0.6938962 0.2741073 0.2570091 0.1170477
[,25] [,26] [,27] [,28] [,29] [,30]
Predicted 11.4686306 10.7257563 10.5634439 10.5097753 10.52418010 10.6751001
cvpred 11.4715795 10.7304231 10.5651537 10.5201997 10.53094927 10.6765189
LNMEDHVAL 11.4186148 10.8356516 11.0681996 10.3981838 10.61888534 10.8056794
CV residual -0.0529647 0.1052285 0.5030459 -0.1220159 0.08793607 0.1291605
[,31] [,32] [,33] [,34] [,35]
Predicted 10.5830832 10.78347838 10.6365273 10.9249045 11.084537429
cvpred 10.5849531 10.78444039 10.6415184 10.9285328 11.085505985
LNMEDHVAL 10.7077288 10.79753268 10.7684850 11.0603687 11.094375117
CV residual 0.1227756 0.01309229 0.1269666 0.1318359 0.008869132
[,36] [,37] [,38] [,39] [,40] [,41]
Predicted 10.4820092 10.7051809 10.5956544 10.3718419 10.9890025 10.6339459
cvpred 10.4870250 10.7112938 10.5988106 10.3791879 10.9912860 10.6391972
LNMEDHVAL 10.0690020 10.5687495 10.4829060 10.0858091 10.3545632 9.8416121
CV residual -0.4180231 -0.1425443 -0.1159046 -0.2933788 -0.6367228 -0.7975851
[,42] [,43] [,44] [,45] [,46] [,47]
Predicted 10.5890858 10.6796496 10.2422567 11.4818448 11.3865926 10.65452454
cvpred 10.6001507 10.6808911 10.2543726 11.4795631 11.3868464 10.65613179
LNMEDHVAL 9.8469172 10.2327913 10.5213722 11.6386767 11.2437380 10.60410675
CV residual -0.7532335 -0.4480998 0.2669996 0.1591136 -0.1431084 -0.05202504
[,48] [,49] [,50] [,51] [,52] [,53]
Predicted 10.8597488 10.2674539 10.484669 10.4996226 10.889902 10.8483771
cvpred 10.8608242 10.2758550 10.491527 10.5059122 10.891935 10.8521208
LNMEDHVAL 11.1198829 9.9183762 9.942708 10.7121931 11.028417 11.0524760
CV residual 0.2590587 -0.3574788 -0.548819 0.2062809 0.136482 0.2003552
[,54] [,55] [,56] [,57] [,58] [,59]
Predicted 11.0337031 11.06540787 10.9620040 10.419986 10.9714571 11.0254241
cvpred 11.0352511 11.06662357 10.9609488 10.440645 10.9688330 11.0228362
LNMEDHVAL 10.8704714 11.14475614 11.3527567 11.824812 11.3108093 11.3034382
CV residual -0.1647797 0.07813258 0.3918079 1.384168 0.3419763 0.2806021
[,60] [,61] [,62] [,63] [,64]
Predicted 10.651452306 11.07793444 10.41776991 10.396380 10.8629796
cvpred 10.656389816 11.07727548 10.42176516 10.404639 10.8660638
LNMEDHVAL 10.659609532 11.01862914 10.38899537 10.561008 10.5661755
CV residual 0.003219716 -0.05864633 -0.03276979 0.156369 -0.2998883
[,65] [,66] [,67] [,68] [,69]
Predicted 10.590449750 10.7015490 10.58846410 10.9822196 10.7358629
cvpred 10.592842047 10.7016686 10.59199508 10.9850866 10.7389829
LNMEDHVAL 10.584055951 10.1266311 10.62376340 10.4103052 10.4516090
CV residual -0.008786096 -0.5750375 0.03176832 -0.5747815 -0.2873739
[,70] [,71] [,72] [,73] [,74] [,75]
Predicted 10.0915876 10.7150005 10.4817152 10.7801503 10.9562030 10.9774549
cvpred 10.1022122 10.7138265 10.4866705 10.7845398 10.9611632 10.9780595
LNMEDHVAL 10.5050675 10.2819240 10.9818971 11.4710613 11.7174976 10.6572594
CV residual 0.4028554 -0.4319025 0.4952266 0.6865215 0.7563344 -0.3208002
[,76] [,77] [,78] [,79] [,80]
Predicted 10.72062803 10.76360913 10.7953517 10.9219901 10.4937558
cvpred 10.72337737 10.76433094 10.7994882 10.9237631 10.4997874
LNMEDHVAL 10.78725509 10.68966960 10.5347593 10.5713169 10.7705880
CV residual 0.06387772 -0.07466135 -0.2647289 -0.3524462 0.2708007
[,81] [,82] [,83] [,84] [,85] [,86]
Predicted 10.94647218 10.5642353 10.8448008 10.785181 10.545793 10.404114
cvpred 10.94941037 10.5660551 10.8454814 10.784273 10.543748 10.413789
LNMEDHVAL 11.03327546 10.8780472 11.7675677 11.933608 11.959533 10.671278
CV residual 0.08386509 0.3119921 0.9220863 1.149335 1.415785 0.257489
[,87] [,88] [,89] [,90] [,91] [,92]
Predicted 10.5538301 10.312322217 10.7255972 10.8088198 11.1879337 11.1902123
cvpred 10.5548362 10.319047624 10.7281320 10.8158803 11.1854548 11.1905010
LNMEDHVAL 10.2182983 10.315597203 10.6115233 10.6759079 11.4467857 11.2279065
CV residual -0.3365379 -0.003450421 -0.1166087 -0.1399724 0.2613309 0.0374055
[,93] [,94] [,95] [,96] [,97] [,98]
Predicted 10.66785568 10.9355667 10.7436199 10.8088893 10.2421084 10.4171096
cvpred 10.67412190 10.9408963 10.7507933 10.8165649 10.2553765 10.4183758
LNMEDHVAL 10.61643736 10.6358554 10.5078035 10.4429006 10.4222813 10.2819240
CV residual -0.05768454 -0.3050408 -0.2429897 -0.3736643 0.1669048 -0.1364518
[,99] [,100] [,101] [,102] [,103] [,104]
Predicted 10.11868616 10.3463070 10.1772265 10.3241026 10.3462530 10.2066230
cvpred 10.13209857 10.3552514 10.1966718 10.3313347 10.3533438 10.2145164
LNMEDHVAL 10.19241884 10.0562086 10.6406516 10.1425045 9.8521943 9.9987977
CV residual 0.06032028 -0.2990427 0.4439798 -0.1888302 -0.5011495 -0.2157187
[,105] [,106] [,107] [,108] [,109] [,110]
Predicted 10.4352413 10.231665260 10.1231668 10.5375841 10.5288360 10.2753911
cvpred 10.4420176 10.243899981 10.1356901 10.5443462 10.5372057 10.2876203
LNMEDHVAL 10.1023384 10.239959789 9.8730283 9.5956028 9.6091165 10.4716382
CV residual -0.3396792 -0.003940192 -0.2626617 -0.9487434 -0.9280892 0.1840179
[,111] [,112] [,113] [,114] [,115] [,116]
Predicted 10.3814727 10.6991179 10.9010470 10.70956017 12.645063 11.2183619
cvpred 10.3965499 10.7021076 10.9058205 10.71127287 12.643561 11.2180483
LNMEDHVAL 10.1773242 10.3951304 10.5713169 10.72766300 11.984802 11.3952674
CV residual -0.2192256 -0.3069772 -0.3345036 0.01639013 -0.658759 0.1772192
[,117] [,118] [,119] [,120] [,121] [,122]
Predicted 11.5421509 11.5253906 11.0446467 10.573529 11.0159810 11.5473658
cvpred 11.5399096 11.5249824 11.0439132 10.583093 11.0176764 11.5490409
LNMEDHVAL 12.0411980 11.3290026 11.4865815 11.630709 11.4584693 11.3952674
CV residual 0.5012884 -0.1959798 0.4426683 1.047616 0.4407929 -0.1537735
[,123] [,124] [,125] [,126] [,127] [,128]
Predicted 10.9506973 9.5907045 11.29616149 10.3587632 11.2378001 11.2770834
cvpred 10.9480593 9.6166375 11.29375519 10.3679972 11.2366081 11.2785366
LNMEDHVAL 11.4108927 9.8416121 11.21586623 11.0821425 11.0635085 11.9860492
CV residual 0.4628334 0.2249746 -0.07788896 0.7141453 -0.1730996 0.7075126
[,129] [,130] [,131] [,132] [,133] [,134]
Predicted 10.69884155 10.9370385 11.014652 11.1952916 10.90947872 10.4039022
cvpred 10.70493335 10.9368961 11.014251 11.1949565 10.91629671 10.4114315
LNMEDHVAL 10.75577295 11.3337988 11.535665 11.3736634 11.01205017 10.2219413
CV residual 0.05083961 0.3969027 0.521414 0.1787069 0.09575347 -0.1894902
[,135] [,136] [,137] [,138] [,139] [,140]
Predicted 10.346483 10.0532523 10.0464409 9.71454117 10.1439382 10.6717374
cvpred 10.351879 10.0711542 10.0645054 9.73596282 10.1541642 10.6798014
LNMEDHVAL 9.878170 10.2921455 9.2965181 9.76995616 10.9150885 11.3144745
CV residual -0.473709 0.2209913 -0.7679873 0.03399334 0.7609242 0.6346731
[,141] [,142] [,143] [,144] [,145] [,146]
Predicted 9.893313 10.309711 10.80199 10.3786157 10.1496875 10.64279975
cvpred 9.912928 10.314476 10.80549 10.3818762 10.1644300 10.64590491
LNMEDHVAL 11.042922 11.461632 11.06351 9.3842937 9.5178251 10.57131693
CV residual 1.129994 1.147156 0.25802 -0.9975825 -0.6466049 -0.07458799
[,147] [,148] [,149] [,150] [,151] [,152]
Predicted 10.58913 10.2052040 10.399424 10.6585572 10.5501402 9.9949126
cvpred 10.60048 10.2173528 10.409557 10.6615475 10.5506383 10.0123158
LNMEDHVAL 11.18303 9.3413686 10.030120 9.9134379 10.1064284 9.5324239
CV residual 0.58255 -0.8759842 -0.379437 -0.7481097 -0.4442099 -0.4798919
[,153] [,154] [,155] [,156] [,157] [,158]
Predicted 10.2697061 10.0001443 10.7599958 10.0713041 10.7413995 11.166326
cvpred 10.2760155 10.0138486 10.7764791 10.0848751 10.7386211 11.165428
LNMEDHVAL 9.7350689 9.2103404 9.9475044 10.6041067 10.4163112 10.030120
CV residual -0.5409466 -0.8035082 -0.8289747 0.5192317 -0.3223099 -1.135308
[,159] [,160] [,161] [,162] [,163] [,164]
Predicted 11.2699232 10.5475603 10.6507494 10.366328 10.4831515 10.4458476
cvpred 11.2674993 10.5530447 10.6534117 10.373022 10.4892483 10.4504114
LNMEDHVAL 10.7144178 10.7768708 9.8883739 10.229188 9.5539301 10.2681307
CV residual -0.5530815 0.2238261 -0.7650378 -0.143834 -0.9353183 -0.1822807
[,165] [,166] [,167] [,168] [,169] [,170]
Predicted 10.0010878 10.5721981 10.1615600 10.8591232 10.31842654 10.50905183
cvpred 10.0156650 10.5763860 10.1714649 10.8606508 10.32591322 10.51323620
LNMEDHVAL 10.2646524 9.7409686 9.8626656 10.5159668 10.27159687 10.50780352
CV residual 0.2489874 -0.8354174 -0.3087994 -0.3446839 -0.05431635 -0.00543268
[,171] [,172] [,173] [,174] [,175] [,176]
Predicted 10.7597271 10.5637576 10.5049396 10.4893693 10.5912981 10.5361304
cvpred 10.7630039 10.5688753 10.5102397 10.4972909 10.5961799 10.5441161
LNMEDHVAL 9.9522777 9.8574436 9.9758082 9.6803440 9.9475044 9.6677652
CV residual -0.8107262 -0.7114317 -0.5344315 -0.8169469 -0.6486754 -0.8763509
[,177] [,178] [,179] [,180] [,181] [,182]
Predicted 10.3476011 10.279387 10.3032182 10.4252661 10.2877036 10.83340581
cvpred 10.3537395 10.286920 10.3101618 10.4323897 10.2973543 10.83723583
LNMEDHVAL 9.9475044 9.680344 9.7350689 10.1064284 9.8984750 10.79957558
CV residual -0.4062351 -0.606576 -0.5750929 -0.3259613 -0.3988793 -0.03766026
[,183] [,184] [,185] [,186] [,187]
Predicted 10.9748786 10.98625527 11.00536850 10.51001742 10.6313420
cvpred 10.9722568 10.98612864 11.00673648 10.51826718 10.6360302
LNMEDHVAL 10.6666271 10.90227951 10.94729160 10.46310334 10.4716382
CV residual -0.3056297 -0.08384913 -0.05944487 -0.05516384 -0.1643919
[,188] [,189] [,190] [,191] [,192]
Predicted 11.1596441 10.82815984 10.919914452 10.4125378 10.7164875
cvpred 11.1584162 10.82912485 10.917816921 10.4210178 10.7193755
LNMEDHVAL 10.8570741 10.79137881 10.927735426 10.0941079 10.5505908
CV residual -0.3013422 -0.03774604 0.009918504 -0.3269098 -0.1687847
[,193] [,194] [,195] [,196] [,197] [,198]
Predicted 10.41890795 10.6206666 10.4066691 10.3470178 10.7443592 10.37581936
cvpred 10.42476800 10.6251767 10.4107579 10.3536605 10.7415828 10.37981991
LNMEDHVAL 10.33201793 10.3734912 9.8626656 9.8883739 10.2363820 10.31559720
CV residual -0.09275007 -0.2516856 -0.5480923 -0.4652866 -0.5052008 -0.06422271
[,199] [,200] [,201] [,202] [,203] [,204]
Predicted 10.5249736 10.6536352 10.7965775 10.4804449 10.5413382 10.4286658
cvpred 10.5253357 10.6558850 10.8008049 10.4816278 10.5445762 10.4366271
LNMEDHVAL 9.9758082 9.9281802 10.1542463 9.5468126 9.8781697 9.9034876
CV residual -0.5495275 -0.7277049 -0.6465586 -0.9348152 -0.6664065 -0.5331395
[,205] [,206] [,207] [,208] [,209] [,210]
Predicted 10.34287234 10.4750772 10.7631066 10.5016317 11.4607492 11.2572300
cvpred 10.34947834 10.4844278 10.7677863 10.5037912 11.4584533 11.2564850
LNMEDHVAL 10.36091240 10.4103052 10.3320179 10.3320179 11.3120325 11.2822536
CV residual 0.01143406 -0.0741226 -0.4357683 -0.1717733 -0.1464208 0.0257687
[,211] [,212] [,213] [,214] [,215] [,216]
Predicted 11.1851468 12.1420218 11.3144868 12.2222465 12.2049098 11.4366140
cvpred 11.1851860 12.1401829 11.3149630 12.2216197 12.2031131 11.4363127
LNMEDHVAL 11.3782506 11.7737501 11.8726956 12.8818193 13.0634623 12.3514708
CV residual 0.1930645 -0.3664328 0.5577326 0.6601996 0.8603492 0.9151582
[,217] [,218] [,219] [,220] [,221] [,222]
Predicted 13.748310 12.5071778 11.552135 11.2370567 10.9670751 10.9758925
cvpred 13.747549 12.5069914 11.553667 11.2397721 10.9673958 10.9765565
LNMEDHVAL 12.876207 11.9754008 11.225243 11.2721270 11.8371805 11.2593227
CV residual -0.871342 -0.5315906 -0.328424 0.0323549 0.8697847 0.2827662
[,223] [,224] [,225] [,226] [,227] [,228]
Predicted 10.7177592 10.8750129 10.3701691 10.6855443 10.686435 10.7887939
cvpred 10.7234190 10.8794496 10.3738007 10.6929149 10.691764 10.7935681
LNMEDHVAL 11.3896272 11.3034382 11.2683029 10.7099634 10.833681 10.5966347
CV residual 0.6662082 0.4239887 0.8945021 0.0170485 0.141917 -0.1969334
[,229] [,230] [,231] [,232] [,233]
Predicted 10.5297013 10.62832241 11.01386949 11.2954732 10.964801994
cvpred 10.5348730 10.63222967 11.01436109 11.2952354 10.968181158
LNMEDHVAL 10.8277465 10.65490364 11.06507464 11.4865815 10.961277847
CV residual 0.2928734 0.02267397 0.05071355 0.1913461 -0.006903311
[,234] [,235] [,236] [,237] [,238] [,239]
Predicted 11.2371193 11.02690017 10.8519934 10.866294 11.0881101 11.380757
cvpred 11.2359108 11.02578756 10.8534138 10.866559 11.0878760 11.379614
LNMEDHVAL 11.1746516 11.06819964 10.8395809 11.327800 11.1968439 11.233212
CV residual -0.0612592 0.04241208 -0.0138329 0.461241 0.1089679 -0.146402
[,240] [,241] [,242] [,243] [,244] [,245]
Predicted 11.1845775 11.3975587 11.4348467 11.68437728 10.9460290 11.2424884
cvpred 11.1842816 11.3965017 11.4325335 11.68334081 10.9470865 11.2400461
LNMEDHVAL 11.4855543 11.5655179 11.1360478 11.75508702 11.0759697 11.1389590
CV residual 0.3012726 0.1690163 -0.2964856 0.07174621 0.1288832 -0.1010871
[,246] [,247] [,248] [,249] [,250] [,251]
Predicted 11.3720435 10.7862505 11.2198395 11.0073445 10.902459 11.1178041
cvpred 11.3714838 10.7902992 11.2173820 11.0070425 10.903296 11.1183679
LNMEDHVAL 11.4731446 11.0219025 11.0120502 10.8077057 11.012050 10.8512770
CV residual 0.1016608 0.2316033 -0.2053318 -0.1993368 0.108754 -0.2670909
[,252] [,253] [,254] [,255] [,256] [,257]
Predicted 10.90329754 10.8910942 10.7408476 11.6420245 11.4695234 11.30165518
cvpred 10.90557733 10.8923904 10.7445213 11.6398502 11.4699910 11.30137504
LNMEDHVAL 10.94199592 11.1316650 11.0852147 11.8415095 11.8026055 11.25285856
CV residual 0.03641859 0.2392746 0.3406935 0.2016594 0.3326145 -0.04851648
[,258] [,259] [,260] [,261] [,262]
Predicted 11.0972020 11.0588202 11.0360828 10.94181999 10.88809084
cvpred 11.0971142 11.0562547 11.0364995 10.94312222 10.88976501
LNMEDHVAL 11.2305626 10.8742665 10.8628378 10.98019501 10.91326863
CV residual 0.1334484 -0.1819882 -0.1736617 0.03707279 0.02350362
[,263] [,264] [,265] [,266] [,267] [,268]
Predicted 10.94484136 11.0942308 11.0377027 10.933357 10.6980221 10.780726
cvpred 10.94745763 11.0952592 11.0398487 10.935270 10.7014171 10.786173
LNMEDHVAL 11.04292184 10.7995756 10.6358554 10.524064 10.8551454 10.929529
CV residual 0.09546421 -0.2956836 -0.4039932 -0.411206 0.1537283 0.143356
[,269] [,270] [,271] [,272] [,273] [,274]
Predicted 10.8678768 11.0218556 10.8360074 10.8982903 11.2561379 10.836679
cvpred 10.8684314 11.0192653 10.8365179 10.8981908 11.2568357 10.840049
LNMEDHVAL 11.0316586 10.6896696 10.6619542 10.5941316 10.9577996 10.635855
CV residual 0.1632273 -0.3295957 -0.1745637 -0.3040592 -0.2990361 -0.204194
[,275] [,276] [,277] [,278] [,279] [,280]
Predicted 11.2524380 11.1120532 11.4355604 10.4029057 11.0062213 10.71968069
cvpred 11.2500023 11.1137882 11.4332476 10.4060019 11.0072286 10.72788336
LNMEDHVAL 10.9114455 10.8036489 10.9560559 10.6286178 10.7210623 10.66662710
CV residual -0.3385569 -0.3101393 -0.4771917 0.2226159 -0.2861663 -0.06125625
[,281] [,282] [,283] [,284] [,285]
Predicted 11.0187123 10.65353762 10.90235710 10.747490408 10.60397722
cvpred 11.0214166 10.65639913 10.90255133 10.750461176 10.60755499
LNMEDHVAL 10.5764320 10.73203937 10.83368119 10.755772954 10.69194491
CV residual -0.4449846 0.07564024 -0.06887014 0.005311779 0.08438992
[,286] [,287] [,288] [,289] [,290] [,291]
Predicted 10.94124142 10.5218752 10.796760 10.7302023 10.56115528 10.47183229
cvpred 10.94407620 10.5276492 10.797638 10.7322677 10.56138962 10.47587003
LNMEDHVAL 10.92593848 10.5132531 11.225243 10.3417425 10.49127422 10.41030515
CV residual -0.01813772 -0.0143961 0.427605 -0.3905253 -0.07011541 -0.06556487
[,292] [,293] [,294] [,295] [,296] [,297]
Predicted 11.2801621 10.8093726 10.2529158 11.07186147 10.80462204 10.81121
cvpred 11.2781594 10.8081022 10.2679331 11.07321005 10.80976499 10.81584
LNMEDHVAL 10.9437643 10.5584135 10.4544950 10.98867682 10.79753268 10.98190
CV residual -0.3343951 -0.2496887 0.1865619 -0.08453323 -0.01223231 0.16606
[,298] [,299] [,300] [,301] [,302] [,303]
Predicted 11.3910182 11.0204936 11.2052219 11.06064000 11.18536633 10.8147239
cvpred 11.3886756 11.0199301 11.2053810 11.06034494 11.18614246 10.8159517
LNMEDHVAL 11.0300392 11.3265959 11.0974100 11.04611673 11.25544923 11.3736634
CV residual -0.3586364 0.3066658 -0.1079709 -0.01422821 0.06930678 0.5577117
[,304] [,305] [,306] [,307] [,308] [,309]
Predicted 11.1755065 11.2602056 10.954580 11.1752045 11.06599610 10.95784496
cvpred 11.1747552 11.2601024 10.954108 11.1760190 11.06552791 10.95708050
LNMEDHVAL 11.3713619 11.4019939 11.164785 11.3144745 11.08827754 11.03488966
CV residual 0.1966067 0.1418915 0.210677 0.1384555 0.02274963 0.07780917
[,310] [,311] [,312] [,313] [,314] [,315]
Predicted 11.3486139 11.26103644 11.0979258 11.3771740 11.0903945 10.8151135
cvpred 11.3480549 11.26111715 11.0953865 11.3774800 11.0888218 10.8180744
LNMEDHVAL 11.0332755 11.18719532 11.2185544 11.0898054 11.0556406 11.0619398
CV residual -0.3147794 -0.07392183 0.1231679 -0.2876745 -0.0331812 0.2438654
[,316] [,317] [,318] [,319] [,320] [,321]
Predicted 11.0920141 11.170568 10.69234720 11.3505645 11.10681878 10.92690398
cvpred 11.0932327 11.170171 10.69735712 11.3521193 11.10540035 10.92817207
LNMEDHVAL 10.9869862 10.941996 10.75577295 11.1690257 11.13750448 11.01369898
CV residual -0.1062465 -0.228175 0.05841583 -0.1830936 0.03210413 0.08552691
[,322] [,323] [,324] [,325] [,326]
Predicted 11.11795194 11.0815505 11.148861881 10.9937962 11.43864107
cvpred 11.11689838 11.0808629 11.149412472 10.9936783 11.43807615
LNMEDHVAL 11.03488966 10.9699209 11.156250521 11.3265959 11.47210347
CV residual -0.08200871 -0.1109419 0.006838049 0.3329176 0.03402732
[,327] [,328] [,329] [,330] [,331]
Predicted 11.1319199 11.32187947 11.5107432 11.2128655 11.4856651
cvpred 11.1309167 11.32119251 11.5095827 11.2123730 11.4833859
LNMEDHVAL 11.3586081 11.38509209 11.3862278 11.5415129 11.3504065
CV residual 0.2276914 0.06389958 -0.1233549 0.3291399 -0.1329794
[,332] [,333] [,334] [,335] [,336] [,337]
Predicted 11.718083506 11.178967 11.2137571 11.101908 11.202403 11.1049943
cvpred 11.719981780 11.178004 11.2131351 11.100907 11.202158 11.1043670
LNMEDHVAL 11.728036845 11.397515 11.3884954 9.588777 11.101945 11.7996070
CV residual 0.008055065 0.219511 0.1753603 -1.512130 -0.100213 0.6952401
[,338] [,339] [,340] [,341] [,342] [,343]
Predicted 11.499897 11.4225882 11.39782660 11.27365573 11.6604087 11.2243631
cvpred 11.497627 11.4202667 11.39693235 11.27330512 11.6586267 11.2243643
LNMEDHVAL 11.909686 11.5926604 11.36210258 11.29849385 11.4053403 11.7890409
CV residual 0.412059 0.1723937 -0.03482978 0.02518873 -0.2532865 0.5646766
[,344]
Predicted 11.7391272
cvpred 11.7370181
LNMEDHVAL 11.9150517
CV residual 0.1780336
Sum of squares = 77.17 Mean square = 0.22 n = 344
fold 3
Observations in test set: 344
[,1] [,2] [,3] [,4] [,5] [,6]
Predicted 11.4022482 10.4827527 10.990103 11.2715650 11.162955 12.6869188
cvpred 11.4139802 10.4711200 11.003097 11.2837675 11.168606 12.7395561
LNMEDHVAL 12.1112124 10.9150885 12.323856 11.7027190 12.703509 12.5886102
CV residual 0.6972321 0.4439685 1.320759 0.4189515 1.534903 -0.1509459
[,7] [,8] [,9] [,10] [,11] [,12]
Predicted 11.7948442 10.9562566 11.172259 11.9401301 11.444572 10.64214978
cvpred 11.8191726 10.9615087 11.182198 11.9671697 11.460167 10.64354901
LNMEDHVAL 12.2060726 11.8817266 12.342350 12.4312142 13.130728 10.61398337
CV residual 0.3869001 0.9202179 1.160152 0.4640445 1.670561 -0.02956564
[,13] [,14] [,15] [,16] [,17] [,18]
Predicted 11.42290796 10.8486794 11.209949 10.9984326 10.7018412 10.7204176
cvpred 11.44933461 10.8556347 11.219539 11.0054062 10.7098765 10.7234348
LNMEDHVAL 11.39863632 11.3265959 12.225385 11.7629057 10.2611620 10.0816337
CV residual -0.05069829 0.4709612 1.005846 0.7574995 -0.4487145 -0.6418011
[,19] [,20] [,21] [,22] [,23] [,24]
Predicted 10.3848506 10.630089 11.000769088 11.33224442 10.7826669 10.8556760
cvpred 10.3861347 10.636776 11.005887157 11.34219760 10.7822614 10.8597123
LNMEDHVAL 9.9942419 10.407289 11.002099841 11.40978471 10.8836916 11.1243175
CV residual -0.3918928 -0.229487 -0.003787316 0.06758711 0.1014302 0.2646052
[,25] [,26] [,27] [,28] [,29]
Predicted 10.17817159 10.316216172 10.1541699 10.44984366 10.7587854
cvpred 10.18176408 10.319975303 10.1557993 10.44926018 10.7576649
LNMEDHVAL 10.11455852 10.328755288 9.8146563 10.53209621 10.1542463
CV residual -0.06720556 0.008779985 -0.3411429 0.08283603 -0.6034186
[,30] [,31] [,32] [,33] [,34] [,35]
Predicted 10.519694 11.3120518 10.9897819 11.0686628 10.9323584 11.87340442
cvpred 10.529140 11.3226777 10.9944651 11.0756089 10.9341947 11.89710870
LNMEDHVAL 9.510445 10.8911683 10.6139834 10.9259385 11.3702092 11.83137920
CV residual -1.018695 -0.4315094 -0.3804818 -0.1496704 0.4360144 -0.06572951
[,36] [,37] [,38] [,39] [,40] [,41]
Predicted 10.7498027 10.8712810 10.86937714 11.1150898 11.0517795 11.343305
cvpred 10.7527425 10.8734537 10.86986001 11.1214792 11.0596758 11.355710
LNMEDHVAL 10.9954109 11.1447561 10.90043619 11.0054276 11.6036798 11.227907
CV residual 0.2426684 0.2713025 0.03057618 -0.1160516 0.5440041 -0.127803
[,42] [,43] [,44] [,45] [,46] [,47]
Predicted 10.7189186 11.00144810 10.71469866 11.1795088 11.0390972 10.7533107
cvpred 10.7132869 11.00581887 10.71601238 11.1877708 11.0441862 10.7597969
LNMEDHVAL 11.1287325 10.98867682 10.76214917 11.4731446 10.8257604 10.5505908
CV residual 0.4154456 -0.01714205 0.04613679 0.2853738 -0.2184259 -0.2092061
[,48] [,49] [,50] [,51] [,52] [,53]
Predicted 10.8171554 10.6918457 10.7283872 10.6254168 10.6785381 10.7747380
cvpred 10.8201814 10.6944711 10.7306215 10.6294717 10.6843394 10.7824150
LNMEDHVAL 10.7121931 10.5584135 10.3920676 10.5159668 10.3056138 10.4573727
CV residual -0.1079884 -0.1360576 -0.3385539 -0.1135049 -0.3787256 -0.3250423
[,54] [,55] [,56] [,57] [,58] [,59]
Predicted 10.51934099 10.8940514 10.3818022 10.65992364 10.5227402 10.8585064
cvpred 10.52400851 10.8977673 10.3856934 10.66259650 10.5251399 10.8564217
LNMEDHVAL 10.49404814 10.5789798 10.6016223 10.72985358 10.2146420 11.7852401
CV residual -0.02996037 -0.3187875 0.2159289 0.06725707 -0.3104979 0.9288184
[,60] [,61] [,62] [,63] [,64] [,65]
Predicted 11.2920261 10.8332223 10.7629067 11.4333984 10.5212148 10.43874890
cvpred 11.3097796 10.8374197 10.7634483 11.4459219 10.5306856 10.43996166
LNMEDHVAL 11.6154821 11.3468709 10.5023241 11.1718426 10.6596095 10.51053203
CV residual 0.3057024 0.5094512 -0.2611243 -0.2740793 0.1289239 0.07057037
[,66] [,67] [,68] [,69] [,70] [,71]
Predicted 10.8403640 10.514544 10.8144142 10.5394694 10.6668612 10.7194038
cvpred 10.8473767 10.516675 10.8200491 10.5423958 10.6704490 10.7196000
LNMEDHVAL 10.6873891 10.218298 10.5453414 10.0816337 10.5427064 11.5805841
CV residual -0.1599876 -0.298377 -0.2747077 -0.4607621 -0.1277426 0.8609841
[,72] [,73] [,74] [,75] [,76] [,77]
Predicted 9.766889 10.8184923 10.7901981 11.0025788 10.4903477 10.569437
cvpred 9.765260 10.8213705 10.7973164 11.0085621 10.4910577 10.574482
LNMEDHVAL 11.044521 11.7440372 10.5661755 11.2384886 10.8454460 10.725468
CV residual 1.279261 0.9226667 -0.2311409 0.2299265 0.3543883 0.150986
[,78] [,79] [,80] [,81] [,82] [,83]
Predicted 10.5379191 10.51130437 10.502308 10.5290889 11.0622324 11.3047085
cvpred 10.5413765 10.51086596 10.504720 10.5334034 11.0692202 11.3175808
LNMEDHVAL 10.3449631 10.46024211 10.243525 10.3640720 11.1788504 11.1476421
CV residual -0.1964134 -0.05062385 -0.261195 -0.1693314 0.1096301 -0.1699386
[,84] [,85] [,86] [,87] [,88]
Predicted 12.6264544 10.792254827 10.9883092 10.63108700 10.6139549
cvpred 12.6709466 10.795123428 10.9934460 10.63533238 10.6117068
LNMEDHVAL 12.1756134 10.789319077 11.1718426 10.72546760 10.2072890
CV residual -0.4953332 -0.005804351 0.1783966 0.09013523 -0.4044178
[,89] [,90] [,91] [,92] [,93] [,94]
Predicted 10.4818386 10.654784 10.5446586 10.29757686 10.4542165 10.4158706
cvpred 10.4814266 10.652275 10.5409288 10.29577636 10.4483884 10.4126270
LNMEDHVAL 10.9022795 10.214642 10.3889954 10.39206757 11.0235351 10.2109723
CV residual 0.4208529 -0.437633 -0.1519335 0.09629121 0.5751467 -0.2016547
[,95] [,96] [,97] [,98] [,99] [,100]
Predicted 10.7978296 10.8543625 10.906916 10.4831219 10.8079365 11.2727955
cvpred 10.7991595 10.8546044 10.916514 10.4891150 10.8111972 11.2846317
LNMEDHVAL 10.5213722 10.5294260 10.578980 10.3609124 11.0186291 11.1004357
CV residual -0.2777873 -0.3251784 -0.337534 -0.1282026 0.2074319 -0.1841959
[,101] [,102] [,103] [,104] [,105] [,106]
Predicted 10.4814923 12.1956586 11.102649 10.9070291 10.625177 10.1745820
cvpred 10.4815604 12.2340430 11.106768 10.9134328 10.619205 10.1832599
LNMEDHVAL 10.0604913 12.1281111 13.345507 11.1272630 11.630709 10.2989023
CV residual -0.4210691 -0.1059319 2.238739 0.2138302 1.011503 0.1156424
[,107] [,108] [,109] [,110] [,111] [,112]
Predicted 11.00229236 10.6053772 11.024908 11.7973133 10.3148386 11.0111010
cvpred 11.00386132 10.6125187 11.034402 11.8190841 10.3166588 11.0182755
LNMEDHVAL 10.92952915 11.2897819 12.210563 11.4845260 10.0774409 10.2072890
CV residual -0.07433217 0.6772632 1.176161 -0.3345581 -0.2392179 -0.8109865
[,113] [,114] [,115] [,116] [,117] [,118]
Predicted 10.24011961 9.89706296 10.3311842 10.2156990 10.2547274 9.6991473
cvpred 10.24521830 9.89726054 10.3382563 10.2173181 10.2516879 9.7021238
LNMEDHVAL 10.17351469 9.88328485 10.1425045 9.7526647 9.7925560 9.9617565
CV residual -0.07170361 -0.01397569 -0.1957518 -0.4646534 -0.4591319 0.2596327
[,119] [,120] [,121] [,122] [,123] [,124]
Predicted 10.8868438 10.3348631 11.2331194 10.60835579 10.8460248 10.6126591
cvpred 10.8854791 10.3365146 11.2428107 10.60615747 10.8607660 10.6144718
LNMEDHVAL 11.2708539 11.2476570 10.3889954 10.69194491 10.9835964 10.3254820
CV residual 0.3853748 0.9111424 -0.8538153 0.08578744 0.1228303 -0.2889899
[,125] [,126] [,127] [,128] [,129] [,130]
Predicted 9.565287 10.1774902 10.1645372 10.4925946 10.4250813 10.2890793
cvpred 9.572049 10.1808727 10.1670792 10.4967591 10.4201068 10.2852127
LNMEDHVAL 10.388995 10.5635949 10.5815211 9.7350689 10.0078476 9.4173545
CV residual 0.816946 0.3827221 0.4144419 -0.7616902 -0.4122592 -0.8678582
[,131] [,132] [,133] [,134] [,135] [,136]
Predicted 10.1879537 10.7434147 10.43375537 10.13520206 10.5658135 10.9482064
cvpred 10.1911849 10.7384054 10.44644084 10.13125682 10.5687790 10.9577911
LNMEDHVAL 10.6572594 10.3766113 10.37972173 10.04324949 10.1385597 10.8723707
CV residual 0.4660744 -0.3617941 -0.06671911 -0.08800732 -0.4302193 -0.0854204
[,137] [,138] [,139] [,140] [,141] [,142]
Predicted 10.9972296 11.1534912 10.8794202 10.70075290 10.424186 10.3128717
cvpred 11.0080849 11.1646586 10.8861563 10.70765264 10.434046 10.3166942
LNMEDHVAL 10.9059560 10.8117461 10.6642934 10.80161431 10.295530 9.4649826
CV residual -0.1021289 -0.3529124 -0.2218629 0.09396167 -0.138516 -0.8517116
[,143] [,144] [,145] [,146] [,147] [,148]
Predicted 10.7713952 10.6101562 10.40516509 10.9195584 10.495933 10.2966092
cvpred 10.7670969 10.6087570 10.39977502 10.9260213 10.494544 10.2979271
LNMEDHVAL 9.7699562 9.8883739 10.32548196 10.7726867 9.846917 10.0475879
CV residual -0.9971408 -0.7203831 -0.07429305 -0.1533346 -0.647627 -0.2503392
[,149] [,150] [,151] [,152] [,153] [,154]
Predicted 10.3239518 11.1910379 10.6297193 10.561483 10.6822730 10.2364866
cvpred 10.3231993 11.1987527 10.6291088 10.561700 10.6825239 10.2354442
LNMEDHVAL 9.6290507 10.5105320 10.0212706 10.102338 10.1023384 10.3889954
CV residual -0.6941486 -0.6882207 -0.6078382 -0.459362 -0.5801854 0.1535512
[,155] [,156] [,157] [,158] [,159] [,160]
Predicted 10.1773716 10.5156367 10.2897393 10.3352074 10.4341689 10.31044250
cvpred 10.1786180 10.5131736 10.2935627 10.3324290 10.4331263 10.30597333
LNMEDHVAL 9.8036672 9.7111157 9.4572004 10.2182983 10.2035921 10.36407196
CV residual -0.3749508 -0.8020579 -0.8363622 -0.1141307 -0.2295341 0.05809863
[,161] [,162] [,163] [,164] [,165]
Predicted 10.40439746 10.7859627 11.2318901 11.3092806 10.856985058
cvpred 10.40739460 10.7820346 11.2417057 11.3186503 10.863172198
LNMEDHVAL 10.34174248 9.9330464 11.0445206 10.3889954 10.864751650
CV residual -0.06565211 -0.8489883 -0.1971852 -0.9296549 0.001579452
[,166] [,167] [,168] [,169] [,170] [,171]
Predicted 11.1529014 10.7900362 10.39934542 10.6308256 10.62240058 10.8700985
cvpred 11.1596258 10.7910927 10.39796234 10.6322700 10.62554972 10.8722091
LNMEDHVAL 10.8493371 10.6805162 10.47728798 10.4940481 10.67590791 10.6851034
CV residual -0.3102887 -0.1105765 0.07932563 -0.1382219 0.05035819 -0.1871058
[,172] [,173] [,174] [,175] [,176] [,177]
Predicted 10.5507828 10.3551782 10.5633036 10.7532383 10.5395675 10.623609
cvpred 10.5592899 10.3540218 10.5557603 10.7484787 10.5372365 10.627012
LNMEDHVAL 10.2219413 10.1266311 9.8309169 10.2989023 10.4133127 10.354563
CV residual -0.3373486 -0.2273907 -0.7248435 -0.4495763 -0.1239239 -0.272449
[,178] [,179] [,180] [,181] [,182] [,183]
Predicted 10.5174459 10.4692957 11.0755110 10.3494401 10.4940747 10.7667400
cvpred 10.5132723 10.4643626 11.0867305 10.3520092 10.4992535 10.7708406
LNMEDHVAL 9.9804486 10.0941079 10.6619542 9.9987977 9.8626656 10.5050675
CV residual -0.5328237 -0.3702547 -0.4247763 -0.3532115 -0.6365879 -0.2657731
[,184] [,185] [,186] [,187] [,188] [,189]
Predicted 10.6227098 10.5439555 10.4950961 10.3598426 12.6410326 11.1905837
cvpred 10.6251390 10.5546933 10.4966649 10.3578070 12.6842426 11.2044175
LNMEDHVAL 10.4042628 10.3672216 10.2470773 10.5213722 12.1399328 11.0958937
CV residual -0.2208761 -0.1874717 -0.2495876 0.1635652 -0.5443098 -0.1085238
[,190] [,191] [,192] [,193] [,194] [,195]
Predicted 11.2773866 11.209720 11.5633186 11.1237995 11.2225099 11.0841995
cvpred 11.2888701 11.219435 11.5811310 11.1337771 11.2364710 11.0943619
LNMEDHVAL 11.1109542 11.377106 11.4616322 11.3034382 11.3445068 11.2528586
CV residual -0.1779159 0.157671 -0.1194988 0.1696612 0.1080358 0.1584967
[,196] [,197] [,198] [,199] [,200] [,201]
Predicted 10.9975913 11.4952678 11.26121430 11.20660776 11.0458342 11.3324501
cvpred 11.0049950 11.5160722 11.27353529 11.22176397 11.0518177 11.3453799
LNMEDHVAL 11.2145194 11.3009691 11.22123537 11.19821472 11.5317472 11.6835118
CV residual 0.2095244 -0.2151031 -0.05229992 -0.02354925 0.4799295 0.3381318
[,202] [,203] [,204] [,205] [,206] [,207]
Predicted 14.6284485 12.80869165 11.5106215 11.9716410 12.9322398 11.1123015
cvpred 14.7221596 12.86067570 11.5266871 11.9997010 12.9856804 11.1246506
LNMEDHVAL 13.8155116 12.76568843 11.8988679 12.3131317 12.5954084 11.3805363
CV residual -0.9066481 -0.09498727 0.3721808 0.3134308 -0.3902721 0.2558856
[,208] [,209] [,210] [,211] [,212] [,213]
Predicted 11.55179452 11.6755797 12.5729179 11.37781 10.8584978 10.9622819
cvpred 11.56856483 11.6952810 12.6143971 11.39473 10.8650716 10.9731512
LNMEDHVAL 11.61908566 11.8699004 11.9879166 11.80560 11.2450460 10.5661755
CV residual 0.05052083 0.1746194 -0.6264805 0.41087 0.3799744 -0.4069757
[,214] [,215] [,216] [,217] [,218] [,219]
Predicted 10.820418018 11.0406743 10.5039068 10.5968835 12.551465 10.43398984
cvpred 10.827015478 11.0469749 10.5049629 10.6017634 12.592400 10.44076705
LNMEDHVAL 10.817776282 10.8434948 10.3889954 10.0033329 11.242428 10.36722157
CV residual -0.009239196 -0.2034801 -0.1159675 -0.5984306 -1.349971 -0.07354548
[,220] [,221] [,222] [,223] [,224]
Predicted 11.0453482 10.3240064 11.1605293 10.9340739 10.7825932988
cvpred 11.0553150 10.3221171 11.1675567 10.9439041 10.7899779816
LNMEDHVAL 11.3349943 10.8551454 10.9041194 10.7514994 10.7893190769
CV residual 0.2796792 0.5330284 -0.2634373 -0.1924046 -0.0006589047
[,225] [,226] [,227] [,228] [,229] [,230]
Predicted 11.1669609 11.67742056 11.56403765 11.764694 11.39404297 11.1416888
cvpred 11.1792878 11.69798595 11.58217466 11.785636 11.40780171 11.1518284
LNMEDHVAL 11.0493014 11.66992921 11.51492347 11.930978 11.47210347 11.6457066
CV residual -0.1299864 -0.02805673 -0.06725119 0.145342 0.06430176 0.4938781
[,231] [,232] [,233] [,234] [,235] [,236]
Predicted 12.41848180 11.6407059 11.4797975 11.6809831 11.4774732 11.1292446
cvpred 12.45834956 11.6614210 11.4941111 11.6997979 11.4924043 11.1363929
LNMEDHVAL 12.48218808 11.7729794 11.5463602 11.2305626 11.5038847 11.5109235
CV residual 0.02383852 0.1115584 0.0522491 -0.4692353 0.0114804 0.3745306
[,237] [,238] [,239] [,240] [,241] [,242]
Predicted 11.2440894 11.4639929 11.21660692 11.2857020 11.5610499 10.8510390
cvpred 11.2544796 11.4842901 11.22362170 11.2961352 11.5800654 10.8572045
LNMEDHVAL 11.1169155 11.1360478 11.14186178 11.1094584 11.1576781 10.5840560
CV residual -0.1375641 -0.3482423 -0.08175991 -0.1866768 -0.4223873 -0.2731486
[,243] [,244] [,245] [,246] [,247]
Predicted 11.06711386 11.11266094 11.1648396 11.3849729 10.90641713
cvpred 11.07483674 11.12377502 11.1734197 11.3962660 10.90976797
LNMEDHVAL 11.01862914 11.05879518 11.0413206 10.9577996 10.98698620
CV residual -0.05620759 -0.06497984 -0.1320991 -0.4384664 0.07721824
[,248] [,249] [,250] [,251] [,252]
Predicted 11.3136467 10.914522711 10.5538679 10.57500560 10.98971800
cvpred 11.3231273 10.921113654 10.5619744 10.57276022 10.99608261
LNMEDHVAL 10.9664727 10.915088464 10.9150885 10.53475933 10.96127785
CV residual -0.3566546 -0.006025189 0.3531141 -0.03800089 -0.03480476
[,253] [,254] [,255] [,256] [,257] [,258]
Predicted 10.9001204 10.7607649 10.80118971 10.7993061 10.3434164 10.8753580
cvpred 10.9059681 10.7698719 10.80325740 10.8018371 10.3442211 10.8829541
LNMEDHVAL 10.7493558 10.5687495 10.79753268 10.4072886 10.8395809 10.5635949
CV residual -0.1566122 -0.2011224 -0.00572472 -0.3945485 0.4953598 -0.3193592
[,259] [,260] [,261] [,262] [,263] [,264]
Predicted 9.687306 10.6858659 10.9210086 10.6439269 10.7693276 10.8017642
cvpred 9.695005 10.6833438 10.9256945 10.6409773 10.7715358 10.8028842
LNMEDHVAL 10.714418 10.1619982 10.6310362 10.4163112 10.6358554 10.6501755
CV residual 1.019413 -0.5213456 -0.2946584 -0.2246662 -0.1356803 -0.1527087
[,265] [,266] [,267] [,268] [,269] [,270]
Predicted 10.8662734 10.9122415 11.2500532 10.59422730 10.5235805 11.0266787
cvpred 10.8702797 10.9162072 11.2604366 10.59659136 10.5237646 11.0334020
LNMEDHVAL 10.7054891 11.0413206 11.0728689 10.68510338 11.0169885 10.9004362
CV residual -0.1647905 0.1251134 -0.1875676 0.08851203 0.4932238 -0.1329658
[,271] [,272] [,273] [,274] [,275] [,276]
Predicted 10.8216991 10.4530814 10.5513747 10.8075237 10.7692715 10.706488
cvpred 10.8240436 10.4528621 10.5544018 10.8124724 10.7689835 10.710588
LNMEDHVAL 10.2146420 10.7726867 10.0168162 10.4370527 10.5532052 10.507804
CV residual -0.6094016 0.3198246 -0.5375856 -0.3754197 -0.2157783 -0.202784
[,277] [,278] [,279] [,280] [,281] [,282]
Predicted 10.6905133 10.6139571 11.1752241 11.251637 11.2775432 11.1307310
cvpred 10.6905200 10.6164924 11.1850815 11.260130 11.2879872 11.1417733
LNMEDHVAL 10.5815211 10.5687495 10.8985895 11.456355 11.1287325 11.1169155
CV residual -0.1089989 -0.0477429 -0.2864921 0.196225 -0.1592547 -0.0248578
[,283] [,284] [,285] [,286] [,287] [,288]
Predicted 11.0409362 11.1454510 11.3513397 11.0928923 11.2557575 11.2381470
cvpred 11.0434871 11.1549360 11.3640846 11.1014388 11.2679351 11.2495532
LNMEDHVAL 11.3108093 11.0070874 10.9750712 10.9681983 11.0493014 11.0413206
CV residual 0.2673222 -0.1478486 -0.3890134 -0.1332405 -0.2186337 -0.2082327
[,289] [,290] [,291] [,292] [,293]
Predicted 10.99979203 11.01897240 11.11881941 11.0557276 11.29672702
cvpred 11.00499050 11.02363651 11.12891175 11.0632095 11.30674135
LNMEDHVAL 10.97848998 11.09133097 11.14908203 11.1968439 11.26830288
CV residual -0.02650052 0.06769446 0.02017029 0.1336344 -0.03843847
[,294] [,295] [,296] [,297] [,298] [,299]
Predicted 11.0237826 11.19870108 11.2194920 10.8540938 11.2168517 11.0861182
cvpred 11.0277620 11.20757579 11.2316153 10.8556137 11.2276156 11.0943363
LNMEDHVAL 11.1732481 11.18719532 10.9886768 11.0300392 10.9970873 10.9366720
CV residual 0.1454861 -0.02038046 -0.2429385 0.1744255 -0.2305283 -0.1576643
[,300] [,301] [,302] [,303] [,304] [,305]
Predicted 11.1098906 10.96987376 10.89799926 11.1387316 11.0809437 11.1029724
cvpred 11.1167087 10.97275847 10.90063590 11.1437675 11.0941782 11.1103022
LNMEDHVAL 10.9954109 11.02353512 10.93667204 10.9384498 10.8551454 10.8723707
CV residual -0.1212979 0.05077665 0.03603614 -0.2053177 -0.2390328 -0.2379315
[,306] [,307] [,308] [,309] [,310]
Predicted 11.206405461 10.8687136 11.0127877 10.97730579 11.09332882
cvpred 11.213161018 10.8742882 11.0146233 10.98293529 11.09721105
LNMEDHVAL 11.203679215 11.0821425 10.2541444 11.02353512 11.12136326
CV residual -0.009481803 0.2078544 -0.7604789 0.04059983 0.02415221
[,311] [,312] [,313] [,314] [,315] [,316]
Predicted 11.19418198 11.32956099 11.3013349 11.0630773 10.8886881 11.1353871
cvpred 11.20376546 11.34065451 11.3128250 11.0687714 10.8928165 11.1425649
LNMEDHVAL 11.22390917 11.29725393 11.5028751 11.3713619 11.4616322 11.6064158
CV residual 0.02014371 -0.04340058 0.1900501 0.3025905 0.5688156 0.4638509
[,317] [,318] [,319] [,320] [,321] [,322]
Predicted 11.7433487 11.385004 11.1897467 11.49599241 11.24105444 11.1976129
cvpred 11.7646905 11.397845 11.1981036 11.51383333 11.25083381 11.2068743
LNMEDHVAL 11.4906799 11.618186 11.6877188 11.47001796 11.33020383 11.4414295
CV residual -0.2740106 0.220341 0.4896152 -0.04381537 0.07937002 0.2345552
[,323] [,324] [,325] [,326] [,327] [,328]
Predicted 11.56381998 11.5692160 11.3658613 11.35191266 11.1782571 10.9993460
cvpred 11.58131354 11.5863377 11.3785388 11.36236562 11.1882953 11.0051235
LNMEDHVAL 11.51192496 11.8593480 11.4804023 11.44892013 11.4306302 11.1462002
CV residual -0.06938857 0.2730104 0.1018634 0.08655452 0.2423349 0.1410767
[,329] [,330] [,331] [,332] [,333] [,334]
Predicted 10.9652794 11.108711 11.39553124 11.2779671 11.42034448 11.1624575
cvpred 10.9708609 11.116162 11.40709256 11.2883350 11.43540660 11.1703865
LNMEDHVAL 11.2318879 11.359774 11.32418334 11.4489201 11.51592097 11.8649898
CV residual 0.2610271 0.243612 -0.08290922 0.1605851 0.08051437 0.6946033
[,335] [,336] [,337] [,338] [,339] [,340]
Predicted 11.2976793 11.6634979 11.3590582 11.3402358 11.2088997 11.4727558
cvpred 11.3083857 11.6818684 11.3718182 11.3523077 11.2178997 11.4862795
LNMEDHVAL 11.5307654 11.9537577 11.6262542 11.5502212 11.3884954 11.3759596
CV residual 0.2223797 0.2718893 0.2544359 0.1979135 0.1705957 -0.1103199
[,341] [,342] [,343] [,344]
Predicted 11.50934255 11.5484154 11.4102229 12.25705056
cvpred 11.52379587 11.5666497 11.4253613 12.29050346
LNMEDHVAL 11.50388472 11.3828168 11.2935249 12.31850807
CV residual -0.01991115 -0.1838329 -0.1318364 0.02800461
Sum of squares = 63.1 Mean square = 0.18 n = 344
fold 4
Observations in test set: 344
[,1] [,2] [,3] [,4] [,5] [,6]
Predicted 11.3222615 10.5199693 10.9470610 11.258722 11.079690 10.865160
cvpred 11.3193244 10.5190772 10.9453993 11.255725 11.077932 10.865120
LNMEDHVAL 11.6404388 10.7144178 11.9427579 12.360080 12.462651 11.998433
CV residual 0.3211144 0.1953405 0.9973586 1.104356 1.384719 1.133314
[,7] [,8] [,9] [,10] [,11] [,12]
Predicted 11.062042 11.32581 10.7068520 10.769263 10.7700588 10.2679979
cvpred 11.060087 11.32347 10.7035672 10.767065 10.7666454 10.2653393
LNMEDHVAL 12.149502 12.48370 11.1139393 11.791314 11.3433227 10.9869862
CV residual 1.089416 1.16023 0.4103721 1.024249 0.5766772 0.7216469
[,13] [,14] [,15] [,16] [,17] [,18]
Predicted 10.7521842 10.7550087 10.4961607 10.5663295 10.71580675 11.094104
cvpred 10.7491365 10.7524478 10.4919315 10.5612089 10.71320886 11.092038
LNMEDHVAL 11.1004357 11.6217799 10.7232674 10.8666619 10.78311430 11.332602
CV residual 0.3512992 0.8693321 0.2313359 0.3054529 0.06990544 0.240564
[,19] [,20] [,21] [,22] [,23] [,24]
Predicted 11.0499765 10.3774424 10.9867631 11.3591306 10.9613676 10.88655664
cvpred 11.0484227 10.3720109 10.9826982 11.3564903 10.9597472 10.88503754
LNMEDHVAL 11.2091140 10.8609202 11.4008760 11.0524760 11.1533893 10.95430918
CV residual 0.1606913 0.4889093 0.4181777 -0.3040142 0.1936421 0.06927164
[,25] [,26] [,27] [,28] [,29] [,30]
Predicted 10.6280524 10.46557790 10.9035750 10.7186844 10.0382317 10.3169417
cvpred 10.6262417 10.46293389 10.9012598 10.7166825 10.0343701 10.3154188
LNMEDHVAL 10.7428972 10.37036129 10.2681307 9.8984750 10.9277354 10.6334487
CV residual 0.1166555 -0.09257261 -0.6331292 -0.8182075 0.8933653 0.3180299
[,31] [,32] [,33] [,34] [,35] [,36]
Predicted 10.9104922 11.454768 10.83989397 10.5751724 10.79644515 11.2364011
cvpred 10.9092026 11.451797 10.83834570 10.5727197 10.79459677 11.2353298
LNMEDHVAL 10.4544950 11.336188 10.87993221 10.1961572 10.89302875 10.9595402
CV residual -0.4547076 -0.115609 0.04158651 -0.3765625 0.09843197 -0.2757896
[,37] [,38] [,39] [,40] [,41]
Predicted 10.91592500 10.9192051 10.855281606 11.3321803 11.3652589
cvpred 10.91359007 10.9170842 10.853763957 11.3303155 11.3636033
LNMEDHVAL 10.87615862 10.8016143 10.860920228 11.1858093 11.7174976
CV residual -0.03743145 -0.1154699 0.007156271 -0.1445062 0.3538943
[,42] [,43] [,44] [,45] [,46] [,47]
Predicted 11.0209449 11.17241942 10.9852334 11.2050275 11.0073095 10.9166219
cvpred 11.0199239 11.17024104 10.9835570 11.2026222 11.0050321 10.9139183
LNMEDHVAL 11.7973522 11.15338929 11.3349943 10.6896696 10.7099634 10.4829060
CV residual 0.7774284 -0.01685175 0.3514372 -0.5129526 -0.2950686 -0.4310123
[,48] [,49] [,50] [,51] [,52] [,53]
Predicted 10.4312972 10.7738537 10.9304735 10.5165822 10.89850962 10.64958182
cvpred 10.4267237 10.7710269 10.9281514 10.5147993 10.89646718 10.64679008
LNMEDHVAL 10.7536385 10.5159668 10.5294260 10.4012279 10.81376021 10.68738910
CV residual 0.3269148 -0.2550601 -0.3987254 -0.1135714 -0.08270697 0.04059902
[,54] [,55] [,56] [,57] [,58] [,59]
Predicted 10.7051599 10.8590528 10.48286103 10.58759120 10.9308070 10.4587212
cvpred 10.7003663 10.8535129 10.48253817 10.58622091 10.9277709 10.4551032
LNMEDHVAL 10.5453414 10.6896696 10.44871460 10.66895539 10.4995730 9.8678604
CV residual -0.1550249 -0.1638433 -0.03382356 0.08273448 -0.4281979 -0.5872428
[,60] [,61] [,62] [,63] [,64] [,65]
Predicted 11.1748807 10.7555889 10.71889462 10.61106013 10.9001938 10.4023198
cvpred 11.1719201 10.7530769 10.71526863 10.60645938 10.9000558 10.3972375
LNMEDHVAL 10.6572594 10.5400644 10.62861778 10.63344871 10.3545632 10.6139834
CV residual -0.5146607 -0.2130125 -0.08665085 0.02698933 -0.5454926 0.2167459
[,66] [,67] [,68] [,69] [,70] [,71]
Predicted 10.4856201 10.4929939 10.71316640 10.63497859 10.6504915 10.784252
cvpred 10.4808511 10.4918501 10.70948303 10.63183888 10.6489200 10.782052
LNMEDHVAL 10.2470773 10.9490506 10.80770570 10.56617553 10.4829060 10.645425
CV residual -0.2337738 0.4572005 0.09822268 -0.06566336 -0.1660141 -0.136627
[,72] [,73] [,74] [,75] [,76] [,77]
Predicted 10.8564119 10.863824 10.50297399 10.6275755 10.52128002 10.7583503
cvpred 10.8544493 10.861538 10.49976466 10.6252776 10.51854162 10.7562522
LNMEDHVAL 10.7342204 10.652542 10.51596683 11.1331281 10.61152335 11.3997568
CV residual -0.1202289 -0.208996 0.01620217 0.5078505 0.09298172 0.6435046
[,78] [,79] [,80] [,81] [,82] [,83]
Predicted 10.375918 10.503823 10.7895521 10.7832047 10.557581 10.64411283
cvpred 10.372090 10.503598 10.7897212 10.7828346 10.557362 10.64065005
LNMEDHVAL 11.461632 11.373663 11.3302038 11.5588544 12.221454 10.56617553
CV residual 1.089542 0.870065 0.5404826 0.7760198 1.664092 -0.07447453
[,84] [,85] [,86] [,87] [,88] [,89]
Predicted 10.2032859 10.7821937 10.37450224 10.7285230 10.2459399 10.5139171
cvpred 10.1984150 10.7792629 10.37086283 10.7252299 10.2428579 10.5130253
LNMEDHVAL 10.3889954 10.4829060 10.38899537 10.5479696 10.4193007 10.2921455
CV residual 0.1905803 -0.2963569 0.01813254 -0.1772604 0.1764428 -0.2208797
[,90] [,91] [,92] [,93] [,94] [,95]
Predicted 11.21955781 11.2675302 10.94074072 10.627497 10.7301295 11.0176534
cvpred 11.21761107 11.2663725 10.93786514 10.624011 10.7279959 11.0155787
LNMEDHVAL 11.17605315 11.0332755 10.91144547 10.236382 10.9077892 10.7913788
CV residual -0.04155792 -0.2330971 -0.02641967 -0.387629 0.1797933 -0.2241999
[,96] [,97] [,98] [,99] [,100] [,101]
Predicted 10.48899269 10.2094272 10.2992189 10.347519 10.3623624 10.3209396
cvpred 10.48681428 10.2052197 10.2950514 10.344494 10.3577489 10.3170978
LNMEDHVAL 10.40426284 10.3221979 10.6334487 10.021271 10.0388922 10.5240640
CV residual -0.08255144 0.1169781 0.3383973 -0.323223 -0.3188567 0.2069663
[,102] [,103] [,104] [,105] [,106] [,107]
Predicted 10.38318146 10.5831283 10.8445742 11.13594039 10.5994776 11.0726112
cvpred 10.38267062 10.5800844 10.8421727 11.13416626 10.5980635 11.0702149
LNMEDHVAL 10.45160896 10.7009947 10.7320394 11.09589372 10.9402244 11.1899616
CV residual 0.06893834 0.1209103 -0.1101333 -0.03827254 0.3421609 0.1197467
[,108] [,109] [,110] [,111] [,112] [,113]
Predicted 11.3206104 11.3997402 11.1508947 11.44484 11.38144091 10.780148
cvpred 11.3184790 11.3964262 11.1484536 11.44319 11.37905052 10.780343
LNMEDHVAL 11.1198829 11.1619485 11.0235351 11.95633 11.43927892 11.350407
CV residual -0.1985961 -0.2344777 -0.1249185 0.51314 0.06022841 0.570063
[,114] [,115] [,116] [,117] [,118] [,119]
Predicted 10.3575148 10.7634187 10.9091847 10.6962413 11.229330 11.3714609
cvpred 10.3499039 10.7636604 10.9085472 10.6934577 11.226515 11.3689266
LNMEDHVAL 11.2332116 11.3083583 11.2332116 11.3862278 12.611538 12.1489731
CV residual 0.8833077 0.5446979 0.3246644 0.6927701 1.385023 0.7800465
[,120] [,121] [,122] [,123] [,124] [,125]
Predicted 10.4465340 10.8677592 11.2014704 11.2889674 10.5970419 10.3985541
cvpred 10.4448962 10.8638009 11.1992322 11.2865403 10.5958363 10.3925508
LNMEDHVAL 10.2219413 10.7298536 11.6199845 11.7814247 10.3449631 10.9150885
CV residual -0.2229549 -0.1339473 0.4207524 0.4948844 -0.2508732 0.5225377
[,126] [,127] [,128] [,129] [,130] [,131]
Predicted 10.1240607 9.7651474 10.378955 10.64348980 10.4359098 10.9364701
cvpred 10.1184981 9.7587653 10.376064 10.64307377 10.4344816 10.9343467
LNMEDHVAL 9.5539301 9.5178251 9.769956 10.70996342 10.6572594 11.1633680
CV residual -0.5645681 -0.2409403 -0.606108 0.06688964 0.2227777 0.2290213
[,132] [,133] [,134] [,135] [,136] [,137]
Predicted 10.78579051 11.2572959 10.6117191 11.4948170 11.37564 10.2818938
cvpred 10.78282005 11.2556982 10.6089455 11.4930284 11.37030 10.2791108
LNMEDHVAL 10.79957558 11.0332755 10.2819240 11.2158662 10.48010 9.4649826
CV residual 0.01675552 -0.2224228 -0.3270215 -0.2771622 -0.89020 -0.8141282
[,138] [,139] [,140] [,141] [,142]
Predicted 10.2063331 10.72413345 10.337195912 10.7270000 10.35961371
cvpred 10.2024073 10.71938292 10.333827195 10.7273427 10.35596708
LNMEDHVAL 10.4193007 10.74720759 10.332017934 10.0212706 10.37661131
CV residual 0.2168934 0.02782467 -0.001809262 -0.7060721 0.02064423
[,143] [,144] [,145] [,146] [,147]
Predicted 11.4867356 10.9994120 10.5035930 10.43325535 10.580192090
cvpred 11.4849694 10.9972599 10.5003220 10.42866720 10.578923105
LNMEDHVAL 10.9869862 10.7995756 10.8376182 10.38899537 10.586584397
CV residual -0.4979832 -0.1976844 0.3372962 -0.03967183 0.007661292
[,148] [,149] [,150] [,151] [,152] [,153]
Predicted 10.9955322 10.9841201 10.12375222 10.5801387 10.5627760 10.1649555
cvpred 10.9931509 10.9814991 10.12007456 10.5783119 10.5606821 10.1618666
LNMEDHVAL 10.6596095 10.7954856 10.13459927 10.1658518 9.8626656 9.5609972
CV residual -0.3335414 -0.1860136 0.01452471 -0.4124601 -0.6980165 -0.6008693
[,154] [,155] [,156] [,157] [,158] [,159]
Predicted 10.5772203 10.1990521 10.3279880 10.5892761 9.167831 10.3687287
cvpred 10.5760538 10.1958603 10.3265521 10.5895011 9.156307 10.3674155
LNMEDHVAL 9.7642255 9.5396441 9.6989204 9.6023825 10.221941 10.2435249
CV residual -0.8118283 -0.6562162 -0.6276317 -0.9871186 1.065635 -0.1238906
[,160] [,161] [,162] [,163] [,164] [,165]
Predicted 10.1943256 10.3534299 10.795027 10.1657629 10.4608072 10.533664
cvpred 10.1915667 10.3486904 10.794609 10.1608595 10.4583327 10.530767
LNMEDHVAL 9.9758082 9.5324239 9.510445 9.9330464 9.9475044 9.913438
CV residual -0.2157585 -0.8162665 -1.284164 -0.2278131 -0.5108282 -0.617329
[,166] [,167] [,168] [,169] [,170] [,171]
Predicted 10.3547629 10.8580188 10.6870747 10.5176927 11.074832 10.0334492
cvpred 10.3521410 10.8568552 10.6854142 10.5151754 11.073742 10.0287822
LNMEDHVAL 10.2109723 10.4042628 10.2363820 9.6421228 9.717158 9.6023825
CV residual -0.1411688 -0.4525924 -0.4490322 -0.8730526 -1.356585 -0.4263997
[,172] [,173] [,174] [,175] [,176] [,177]
Predicted 10.4582406 10.4521917 10.2747357 10.38977098 10.4018683 11.0568621
cvpred 10.4558193 10.4490972 10.2723429 10.38659799 10.3993935 11.0543165
LNMEDHVAL 9.9522777 10.2819240 9.9281802 10.34817337 9.7526647 10.6782147
CV residual -0.5035415 -0.1671732 -0.3441627 -0.03842462 -0.6467288 -0.3761017
[,178] [,179] [,180] [,181] [,182] [,183]
Predicted 10.36846025 10.891336 10.88366523 10.80737587 10.8740035 10.8045071
cvpred 10.36710593 10.891222 10.88131015 10.80507896 10.8727101 10.8027584
LNMEDHVAL 10.42228135 9.740969 10.79957558 10.82177629 10.2435249 10.9664727
CV residual 0.05517541 -1.150254 -0.08173457 0.01669732 -0.6291853 0.1637142
[,184] [,185] [,186] [,187] [,188]
Predicted 11.077676228 10.88465104 10.98008719 10.7009732 10.85011014
cvpred 11.076298508 10.88341588 10.97838339 10.6991861 10.85011114
LNMEDHVAL 11.082142549 10.94376426 10.92052819 10.5840560 10.82774645
CV residual 0.005844041 0.06034839 -0.05785521 -0.1151302 -0.02236468
[,189] [,190] [,191] [,192] [,193] [,194]
Predicted 11.1496771 10.7886435 10.754991 10.99179704 10.73884856 10.86180289
cvpred 11.1482173 10.7878085 10.752373 10.99140474 10.73798358 10.86070105
LNMEDHVAL 10.8742665 10.4341158 10.638256 10.89858946 10.79343431 10.84739345
CV residual -0.2739508 -0.3536927 -0.114117 -0.09281527 0.05545073 -0.01330759
[,195] [,196] [,197] [,198] [,199] [,200]
Predicted 10.85200020 10.9971630 10.5630560 10.5008202 10.7417027 10.8558420
cvpred 10.84950443 10.9956633 10.5612676 10.4977123 10.7392310 10.8537615
LNMEDHVAL 10.76214917 10.7099634 10.4163112 10.2576594 10.3385115 10.3089527
CV residual -0.08735525 -0.2856999 -0.1449564 -0.2400529 -0.4007196 -0.5448088
[,201] [,202] [,203] [,204] [,205] [,206]
Predicted 10.7145699 10.6883110 10.5343980 10.558596 10.0018716 10.2588315
cvpred 10.7116659 10.6866002 10.5323587 10.555515 9.9959118 10.2557519
LNMEDHVAL 10.2255711 10.2255711 9.9804486 10.685103 9.7925560 10.4282161
CV residual -0.4860949 -0.4610292 -0.5519101 0.129588 -0.2033558 0.1724641
[,207] [,208] [,209] [,210] [,211] [,212]
Predicted 10.9294020 10.7388314 10.730806 11.048683 11.3640979 11.1068132
cvpred 10.9264197 10.7354239 10.730034 11.045394 11.3613995 11.1053636
LNMEDHVAL 10.1581298 10.0899671 12.251046 11.254155 11.2593227 11.4574128
CV residual -0.7682899 -0.6454568 1.521012 0.208761 -0.1020767 0.3520491
[,213] [,214] [,215] [,216] [,217]
Predicted 11.9171279 11.33407061 11.2647711 11.2026061534 11.2987299
cvpred 11.9141671 11.33272821 11.2630223 11.2016286811 11.2967263
LNMEDHVAL 11.6307085 11.25156070 11.3816772 11.2009506999 11.6342578
CV residual -0.2834586 -0.08116751 0.1186548 -0.0006779811 0.3375314
[,218] [,219] [,220] [,221] [,222] [,223]
Predicted 11.3152038 11.50606801 11.494817 11.385449 13.3762495 11.4290110
cvpred 11.3127888 11.50424817 11.493028 11.382989 13.3686170 11.4263488
LNMEDHVAL 11.5424843 11.47106126 11.723996 12.888664 12.8463463 11.9381932
CV residual 0.2296955 -0.03318691 0.230968 1.505675 -0.5222707 0.5118444
[,224] [,225] [,226] [,227] [,228] [,229]
Predicted 11.0310303 11.249934128 10.6990118 11.0866858 10.6541814 10.7275156
cvpred 11.0255316 11.247516181 10.6955353 11.0837685 10.6511562 10.7256256
LNMEDHVAL 11.3302038 11.250261155 10.8551454 11.6613455 10.9114455 10.5687495
CV residual 0.3046722 0.002744974 0.1596101 0.5775769 0.2602893 -0.1568761
[,230] [,231] [,232] [,233] [,234] [,235]
Predicted 11.0386934 10.8701707 10.64685937 10.59526869 10.507751 10.5799403
cvpred 11.0375563 10.8669102 10.64599446 10.59346055 10.505944 10.5761691
LNMEDHVAL 10.7600283 11.0136990 10.58658440 10.61888534 10.835652 10.8551454
CV residual -0.2775281 0.1467888 -0.05941006 0.02542479 0.329708 0.2789763
[,236] [,237] [,238] [,239] [,240]
Predicted 10.8145950808 10.9444179 10.8575576 10.6905131 10.5817392
cvpred 10.8103331288 10.9429533 10.8556411 10.6879646 10.5785005
LNMEDHVAL 10.8097279486 11.0348897 10.5916222 10.8336812 10.7363967
CV residual -0.0006051803 0.0919364 -0.2640189 0.1457166 0.1578961
[,241] [,242] [,243] [,244] [,245]
Predicted 10.88996539 11.52949580 12.0213465 11.2975068 11.4656518
cvpred 10.88839860 11.52610114 12.0180964 11.2945811 11.4633779
LNMEDHVAL 10.96474405 11.61005218 11.8600550 11.6977439 11.7248058
CV residual 0.07634545 0.08395104 -0.1580414 0.4031628 0.2614279
[,246] [,247] [,248] [,249] [,250] [,251]
Predicted 11.17416474 10.7534147 11.2914227 11.254762 11.3150363 11.35447352
cvpred 11.17276106 10.7511619 11.2894062 11.252667 11.3130134 11.35307449
LNMEDHVAL 11.19958365 11.3702092 11.1476421 11.233212 11.4957793 11.44998567
CV residual 0.02682259 0.6190473 -0.1417641 -0.019455 0.1827659 0.09691118
[,252] [,253] [,254] [,255] [,256] [,257]
Predicted 11.2337674 11.2978317 11.2803094 11.2786763 11.01659843 11.3725239
cvpred 11.2317528 11.2950565 11.2783327 11.2774876 11.01453465 11.3694169
LNMEDHVAL 11.4499857 11.0202671 11.1139393 10.7851868 10.92413830 11.1619485
CV residual 0.2182328 -0.2747894 -0.1643934 -0.4923008 -0.09039635 -0.2074684
[,258] [,259] [,260] [,261] [,262] [,263]
Predicted 11.098282613 10.95786618 11.315398 11.1659464 11.6150515 11.1649699
cvpred 11.097594727 10.95560807 11.312741 11.1640633 11.6129291 11.1640969
LNMEDHVAL 11.100435742 11.02026715 11.724806 11.6036798 11.2463524 10.8609202
CV residual 0.002841015 0.06465907 0.412065 0.4396165 -0.3665768 -0.3031767
[,264] [,265] [,266] [,267] [,268] [,269]
Predicted 10.9595738 10.85485062 10.8322300 10.6701887 10.94976 10.9290030
cvpred 10.9571630 10.85309116 10.8308323 10.6681461 10.94784 10.9268950
LNMEDHVAL 10.8415398 10.83761820 10.9313197 11.0666384 10.63826 10.5347593
CV residual -0.1156232 -0.01547296 0.1004873 0.3984922 -0.30958 -0.3921357
[,270] [,271] [,272] [,273] [,274]
Predicted 10.82105385 10.6407846 10.9349816 10.6265217 10.72042338
cvpred 10.81883288 10.6371976 10.9334565 10.6249510 10.71995679
LNMEDHVAL 10.89488576 10.4857032 10.6139834 10.5050675 10.73856823
CV residual 0.07605288 -0.1514944 -0.3194732 -0.1198835 0.01861144
[,275] [,276] [,277] [,278] [,279]
Predicted 10.754169709351 10.8492892 11.2379724 11.0413096 10.86856478
cvpred 10.751505212415 10.8477713 11.2362255 11.0388841 10.86663560
LNMEDHVAL 10.751499443657 10.6237634 10.9801950 10.8589990 10.81777628
CV residual -0.000005768758 -0.2240079 -0.2560305 -0.1798851 -0.04885932
[,280] [,281] [,282] [,283] [,284]
Predicted 11.9718086 10.63828417 10.40670996 10.759031025 10.65643727
cvpred 11.9686959 10.63582125 10.40401025 10.756517779 10.65351856
LNMEDHVAL 11.4521133 10.60162227 10.38282251 10.766377508 10.57643203
CV residual -0.5165826 -0.03419897 -0.02118774 0.009859728 -0.07708653
[,285] [,286] [,287] [,288] [,289] [,290]
Predicted 10.99229220 11.3966060 10.7495229 11.0391322 11.1313670 10.9629357
cvpred 10.98984490 11.3948370 10.7498031 11.0371434 11.1299745 10.9613067
LNMEDHVAL 10.96127785 11.2252434 10.9277354 10.9767820 11.0004318 11.1830315
CV residual -0.02856705 -0.1695936 0.1779323 -0.0603614 -0.1295428 0.2217248
[,291] [,292] [,293] [,294] [,295] [,296]
Predicted 11.6582502 11.0375227 11.3786338 11.31419246 11.0905644 11.04472841
cvpred 11.6560080 11.0362150 11.3771677 11.31290524 11.0884683 11.04305035
LNMEDHVAL 11.4957793 11.3702092 11.6647878 11.34922937 10.9472916 10.95779958
CV residual -0.1602287 0.3339941 0.2876202 0.03632413 -0.1411767 -0.08525077
[,297] [,298] [,299] [,300] [,301] [,302]
Predicted 11.13588563 11.2625792 10.8618907 11.2207211 11.1078255 11.2701414
cvpred 11.13372223 11.2606385 10.8603317 11.2196933 11.1060151 11.2675008
LNMEDHVAL 11.04132055 11.0136990 10.9277354 11.0381103 10.9733574 11.0219025
CV residual -0.09240167 -0.2469395 0.0674037 -0.1815831 -0.1326578 -0.2455983
[,303] [,304] [,305] [,306] [,307] [,308]
Predicted 11.2425409 11.07313581 11.15012283 11.0484974 11.3023742 11.395773
cvpred 11.2410530 11.07251773 11.14851501 11.0465614 11.3002289 11.392573
LNMEDHVAL 11.0635085 11.08827754 11.04930144 11.2997322 11.1760531 11.219896
CV residual -0.1775446 0.01575981 -0.09921357 0.2531709 -0.1241757 -0.172677
[,309] [,310] [,311] [,312] [,313]
Predicted 11.0695323 11.03323039 10.92304183 10.7590093 10.794055214
cvpred 11.0685986 11.03204785 10.92131058 10.7572422 10.791914097
LNMEDHVAL 10.9384498 10.99541085 10.97164063 11.0397167 10.793434309
CV residual -0.1301488 -0.03663699 0.05033006 0.2824745 0.001520212
[,314] [,315] [,316] [,317] [,318] [,319]
Predicted 11.1407992 10.9749671 11.21391444 10.7484315 11.23148380 11.201385
cvpred 11.1381771 10.9728542 11.21121713 10.7462020 11.22945905 11.199660
LNMEDHVAL 10.9187182 11.2631812 11.12136326 10.9384498 11.18024603 11.501865
CV residual -0.2194589 0.2903271 -0.08985387 0.1922479 -0.04921302 0.302205
[,320] [,321] [,322] [,323] [,324] [,325]
Predicted 11.1241730 11.5935361 11.1089335 11.1457594 11.3496413 11.0167021
cvpred 11.1226849 11.5914734 11.1072233 11.1433878 11.3472374 11.0160138
LNMEDHVAL 11.5199011 11.4626842 11.3445068 11.4637352 11.5559850 11.4700180
CV residual 0.3972162 -0.1287892 0.2372835 0.3203475 0.2087475 0.4540042
[,326] [,327] [,328] [,329] [,330] [,331]
Predicted 10.9257142 11.1579800 12.0848852 11.49255488 11.4373822 10.7014923
cvpred 10.9236086 11.1571264 12.0814587 11.49035944 11.4353931 10.6997092
LNMEDHVAL 11.4403548 11.5385932 12.0376540 11.51592097 11.3748122 10.9784900
CV residual 0.5167462 0.3814668 -0.0438047 0.02556154 -0.0605809 0.2787808
[,332] [,333] [,334] [,335] [,336] [,337]
Predicted 11.4528762 11.2193150 11.4574819 11.1900435 11.2871872 11.0960735
cvpred 11.4504228 11.2173619 11.4550910 11.1873324 11.2853916 11.0947423
LNMEDHVAL 11.3678997 11.6190857 11.3456895 11.4338823 11.3805363 11.5444241
CV residual -0.0825231 0.4017237 -0.1094015 0.2465498 0.0951447 0.4496819
[,338] [,339] [,340] [,341] [,342] [,343]
Predicted 10.9141045 10.9483789 11.3153178 11.53230632 11.8828125 11.28943117
cvpred 10.9128093 10.9470381 11.3118599 11.53041365 11.8795250 11.28708584
LNMEDHVAL 11.4689736 11.4119995 11.4403548 11.57683879 11.6647878 11.35627165
CV residual 0.5561642 0.4649615 0.1284949 0.04642514 -0.2147372 0.06918581
[,344]
Predicted 11.2219867
cvpred 11.2198645
LNMEDHVAL 11.8277362
CV residual 0.6078717
Sum of squares = 63.64 Mean square = 0.18 n = 344
fold 5
Observations in test set: 344
[,1] [,2] [,3] [,4] [,5] [,6]
Predicted 11.21492 10.446765 11.178997 10.9294588 11.054480 11.03020
cvpred 11.20197 10.442695 11.166511 10.9208784 11.041259 11.02019
LNMEDHVAL 12.32386 11.745623 12.177673 10.6873891 12.323856 12.88512
CV residual 1.12189 1.302928 1.011162 -0.2334893 1.282597 1.86493
[,7] [,8] [,9] [,10] [,11] [,12]
Predicted 10.626329 10.731197 11.5164940 11.121032 11.2190838 11.001200
cvpred 10.619994 10.723118 11.5057215 11.110571 11.2113591 10.990580
LNMEDHVAL 11.844385 12.008231 12.2788583 12.487485 12.0100578 12.261034
CV residual 1.224391 1.285113 0.7731368 1.376914 0.7986987 1.270454
[,13] [,14] [,15] [,16] [,17] [,18]
Predicted 11.2337888 11.3837992 10.984028 10.7576134 10.39274271 10.6234523
cvpred 11.2227903 11.3716472 10.970277 10.7509370 10.38478266 10.6140982
LNMEDHVAL 11.4927228 12.0482486 11.982929 10.9886768 10.41030515 10.7144178
CV residual 0.2699324 0.6766014 1.012652 0.2377398 0.02552249 0.1003195
[,19] [,20] [,21] [,22] [,23] [,24]
Predicted 10.5709638 10.2468807 10.7442548 10.94626834 10.2625138 10.3564706
cvpred 10.5628972 10.2347831 10.7346737 10.93955024 10.2509178 10.3482768
LNMEDHVAL 11.0493014 9.8362788 11.1548209 11.03650127 11.0169885 11.2050407
CV residual 0.4864042 -0.3985043 0.4201472 0.09695103 0.7660707 0.8567639
[,25] [,26] [,27] [,28] [,29]
Predicted 11.3839654 10.92898867 10.7275622 10.64234806 10.48223008
cvpred 11.3746315 10.91904723 10.7194873 10.63195386 10.47548424
LNMEDHVAL 11.2252434 10.87804719 10.8628378 10.61398337 10.51867319
CV residual -0.1493881 -0.04100004 0.1433504 -0.01797049 0.04318895
[,30] [,31] [,32] [,33] [,34] [,35]
Predicted 10.7806720 10.6194739 10.4070477 10.49494982 10.5000656 10.3940958
cvpred 10.7735517 10.6129698 10.3996227 10.48753696 10.4924316 10.3847699
LNMEDHVAL 11.0267925 10.4282161 10.1345993 10.51053203 10.2435249 9.7981270
CV residual 0.2532408 -0.1847537 -0.2650234 0.02299507 -0.2489067 -0.5866429
[,36] [,37] [,38] [,39] [,40] [,41]
Predicted 10.7686276 10.452089 10.4718976 9.8467248 11.1310824 11.02717140
cvpred 10.7613793 10.443469 10.4612544 9.8368472 11.1227260 11.01981514
LNMEDHVAL 10.3577428 9.923290 10.0212706 9.4414521 10.8647517 11.00542763
CV residual -0.4036365 -0.520179 -0.4399838 -0.3953951 -0.2579744 -0.01438751
[,42] [,43] [,44] [,45] [,46] [,47]
Predicted 10.652975 10.6929332 10.598329140 10.90810055 11.2607029 10.6528484
cvpred 10.645479 10.6842553 10.589862444 10.90134620 11.2511660 10.6462385
LNMEDHVAL 10.700995 10.4341158 10.599131613 10.85321306 11.2292354 10.9132686
CV residual 0.055516 -0.2501395 0.009269169 -0.04813314 -0.0219306 0.2670301
[,48] [,49] [,50] [,51] [,52] [,53]
Predicted 10.99163815 10.9823989 11.1107290 11.133263 10.97855939 10.7962951
cvpred 10.98408860 10.9737100 11.1023622 11.124447 10.97179032 10.7883912
LNMEDHVAL 11.01698845 11.1139393 11.3314036 10.980195 11.05089001 10.6115233
CV residual 0.03289985 0.1402293 0.2290414 -0.144252 0.07909969 -0.1768678
[,54] [,55] [,56] [,57] [,58]
Predicted 10.70309896 11.01746924 10.89268977 11.1186489 10.9529669
cvpred 10.69555905 11.00806890 10.88227493 11.1116545 10.9408002
LNMEDHVAL 10.65017550 10.97164063 10.78311430 11.2984939 11.4957793
CV residual -0.04538355 -0.03642826 -0.09916063 0.1868394 0.5549792
[,59] [,60] [,61] [,62] [,63] [,64]
Predicted 10.522615254 10.6742325 10.4876073 10.5482367 10.9248006 10.8179917
cvpred 10.517937667 10.6659428 10.4807543 10.5400405 10.9167749 10.8094972
LNMEDHVAL 10.521372249 10.5584135 10.2715969 10.4012279 10.7099634 10.4252531
CV residual 0.003434582 -0.1075293 -0.2091574 -0.1388125 -0.2068115 -0.3842441
[,65] [,66] [,67] [,68] [,69] [,70]
Predicted 10.6527237 10.752237 10.74159016 10.4944482 10.2228133 10.7883419
cvpred 10.6441151 10.742722 10.73244371 10.4854732 10.1996064 10.7807244
LNMEDHVAL 10.2784935 10.454495 10.63585545 10.2921455 10.5320962 11.5768388
CV residual -0.3656217 -0.288227 -0.09658826 -0.1933277 0.3324898 0.7961144
[,71] [,72] [,73] [,74] [,75] [,76]
Predicted 10.9791745 10.9094230 10.8093444 10.9624140 10.681768 10.75001159
cvpred 10.9725051 10.9012535 10.8024781 10.9567503 10.674550 10.74176145
LNMEDHVAL 11.4988265 10.7621492 10.5661755 10.5267486 10.571317 10.72326738
CV residual 0.5263214 -0.1391043 -0.2363026 -0.4300016 -0.103233 -0.01849407
[,77] [,78] [,79] [,80] [,81] [,82]
Predicted 10.8525305 10.77139631 10.73910452 10.4424186 10.8362983 10.14786
cvpred 10.8457804 10.76304288 10.73108044 10.4347104 10.8323094 10.13981
LNMEDHVAL 10.9801950 10.66895539 10.65017550 10.1226231 11.0316586 10.98360
CV residual 0.1344146 -0.09408748 -0.08090494 -0.3120873 0.1993492 0.84379
[,83] [,84] [,85] [,86] [,87] [,88]
Predicted 10.7221587 10.625699 10.575201 10.621183 10.573663 10.773044
cvpred 10.7156223 10.619696 10.570125 10.614958 10.572238 10.763407
LNMEDHVAL 11.0397167 12.178701 11.423001 12.154779 12.323856 11.386228
CV residual 0.3240945 1.559005 0.852876 1.539822 1.751618 0.622821
[,89] [,90] [,91] [,92] [,93] [,94]
Predicted 10.82294 10.5625539 10.6748060 10.5762219 10.4729387 11.2807334
cvpred 10.81513 10.5563953 10.6640687 10.5668878 10.4644769 11.2724070
LNMEDHVAL 12.01491 10.2072890 10.4744671 10.4193007 10.1886665 11.1704352
CV residual 1.19978 -0.3491063 -0.1896016 -0.1475871 -0.2758104 -0.1019718
[,95] [,96] [,97] [,98] [,99] [,100]
Predicted 11.143201398 10.8782058 10.4729752 10.59025557 10.833114 10.7950545
cvpred 11.134548695 10.8699538 10.4664105 10.58487940 10.823648 10.7882326
LNMEDHVAL 11.128732492 11.0300392 10.1849000 10.50780352 10.691945 10.5105320
CV residual -0.005816203 0.1600854 -0.2815105 -0.07707588 -0.131703 -0.2777005
[,101] [,102] [,103] [,104] [,105] [,106]
Predicted 10.9189758 10.1603887 10.5470014 10.2725050 10.3359394 10.2225715
cvpred 10.9117243 10.1494773 10.5421023 10.2639883 10.3248059 10.2161026
LNMEDHVAL 10.2506171 10.3640720 9.6158055 10.2363820 10.5479696 10.0941079
CV residual -0.6611072 0.2145947 -0.9262968 -0.0276063 0.2231637 -0.1219946
[,107] [,108] [,109] [,110] [,111] [,112]
Predicted 10.6264395 10.3650018 10.7352463 10.49252193 10.1139845 10.64378999
cvpred 10.6173196 10.3577949 10.7255986 10.48325109 10.1059701 10.63503487
LNMEDHVAL 10.2541444 10.2989023 9.9987977 10.40728856 10.0647557 10.60905725
CV residual -0.3631751 -0.0588926 -0.7268008 -0.07596252 -0.0412144 -0.02597762
[,113] [,114] [,115] [,116] [,117] [,118]
Predicted 10.6270514 10.8794916 10.97595467 10.94079579 10.8094493 10.8342625
cvpred 10.6219151 10.8726227 10.96716077 10.93117893 10.8015569 10.8268819
LNMEDHVAL 10.3089527 10.8356516 11.03165864 10.96647266 11.6851967 11.0461167
CV residual -0.3129624 -0.0369711 0.06449788 0.03529373 0.8836398 0.2192348
[,119] [,120] [,121] [,122] [,123] [,124]
Predicted 11.006499 10.556586 10.9225940 11.104691 10.9017709 10.432591
cvpred 10.998368 10.552621 10.9117174 11.095521 10.8867420 10.429304
LNMEDHVAL 11.200951 11.082143 11.2580332 11.744037 11.2252434 11.831379
CV residual 0.202583 0.529522 0.3463158 0.648516 0.3385014 1.402075
[,125] [,126] [,127] [,128] [,129] [,130]
Predicted 11.4900326 11.017662 10.6073481 11.0980986 11.007362 11.3054184
cvpred 11.4773960 11.007536 10.5999517 11.0891418 10.997804 11.2968511
LNMEDHVAL 12.2908732 12.291332 10.9348911 11.5327281 11.336188 11.4435754
CV residual 0.8134772 1.283796 0.3349394 0.4435863 0.338384 0.1467243
[,131] [,132] [,133] [,134] [,135] [,136]
Predicted 11.162468 10.0741753 10.6139653 10.2808523 10.4611711 9.6713674
cvpred 11.147037 10.0635919 10.6121463 10.2738906 10.4532248 9.6560439
LNMEDHVAL 9.841612 10.4133127 10.2219413 9.4334839 10.8761586 9.9664624
CV residual -1.305425 0.3497208 -0.3902051 -0.8404067 0.4229338 0.3104184
[,137] [,138] [,139] [,140] [,141] [,142]
Predicted 9.9647654 10.7508256 11.0632540 10.60730163 10.8014067 10.5382060
cvpred 9.9487999 10.7400277 11.0484507 10.59709833 10.7909763 10.5339622
LNMEDHVAL 10.9041194 11.2721270 10.7621492 10.62861778 10.5610076 10.6759079
CV residual 0.9553195 0.5320992 -0.2863015 0.03151945 -0.2299688 0.1419458
[,143] [,144] [,145] [,146] [,147] [,148]
Predicted 11.1984277 11.01690186 10.323070 10.632710 10.3367029 10.3004299
cvpred 11.1904978 11.01115037 10.315889 10.630708 10.3298714 10.2903158
LNMEDHVAL 11.0202671 11.06507464 9.417355 11.742449 10.1226231 9.9942419
CV residual -0.1702306 0.05392427 -0.898534 1.111741 -0.2072483 -0.2960739
[,149] [,150] [,151] [,152] [,153] [,154]
Predicted 10.727637 10.6662168 10.15122756 10.8711454 10.7377564 10.8902677
cvpred 10.721527 10.6543190 10.14416628 10.8610457 10.7294634 10.8825700
LNMEDHVAL 9.692767 10.3545632 10.09823163 10.9903646 10.2255711 10.3889954
CV residual -1.028761 -0.2997558 -0.04593465 0.1293189 -0.5038924 -0.4935747
[,155] [,156] [,157] [,158] [,159] [,160]
Predicted 10.6452205 10.0805100 10.4905030 10.581570 10.591020 10.2995122
cvpred 10.6408182 10.0693991 10.4861254 10.574884 10.582920 10.2899195
LNMEDHVAL 9.9804486 10.3189030 10.0899671 9.375855 9.350102 9.8255260
CV residual -0.6603696 0.2495039 -0.3961583 -1.199029 -1.232818 -0.4643934
[,161] [,162] [,163] [,164] [,165] [,166]
Predicted 10.5588271 10.320654 10.7331580 10.6327268 10.681989 11.0348373
cvpred 10.5540283 10.311943 10.7263786 10.6261720 10.675050 11.0231802
LNMEDHVAL 9.7699562 9.287301 10.3189030 10.4282161 10.232791 10.4429006
CV residual -0.7840721 -1.024642 -0.4074756 -0.1979559 -0.442259 -0.5802796
[,167] [,168] [,169] [,170] [,171] [,172]
Predicted 10.7382297 11.0441305 10.3745931 10.5141542 10.65966 10.8300696
cvpred 10.7317132 11.0359774 10.3695035 10.5073015 10.65379 10.8211293
LNMEDHVAL 10.3828225 10.3385115 10.5267486 10.2291877 10.36722 9.9232902
CV residual -0.3488906 -0.6974659 0.1572451 -0.2781138 -0.28657 -0.8978391
[,173] [,174] [,175] [,176] [,177] [,178]
Predicted 10.3266266 10.3120964 10.5318852 10.4873851 10.40635801 10.88320028
cvpred 10.3209998 10.3056436 10.5239666 10.4773586 10.39933134 10.87520752
LNMEDHVAL 9.5819039 9.7699562 10.3951304 10.2182983 10.46024211 10.78311430
CV residual -0.7390959 -0.5356875 -0.1288363 -0.2590603 0.06091077 -0.09209322
[,179] [,180] [,181] [,182] [,183] [,184]
Predicted 10.7134583 10.5585201 10.6700453 10.6522847 11.0463381 10.5748609
cvpred 10.7057183 10.5516464 10.6629386 10.6429005 11.0382425 10.5628851
LNMEDHVAL 10.8077057 11.0120502 10.5374154 10.4995730 10.7298536 10.4995730
CV residual 0.1019874 0.4604038 -0.1255232 -0.1433275 -0.3083889 -0.0633121
[,185] [,186] [,187] [,188] [,189] [,190]
Predicted 11.2029989 10.5264806 10.6875766 10.5375873 10.8247556 9.9585426
cvpred 11.1937190 10.5213185 10.6833585 10.5322339 10.8185409 9.9519068
LNMEDHVAL 10.9543092 10.6873891 10.3513734 10.0212706 10.4222813 9.4334839
CV residual -0.2394098 0.1660706 -0.3319851 -0.5109633 -0.3962596 -0.5184228
[,191] [,192] [,193] [,194] [,195] [,196]
Predicted 10.5536104 10.61055004 10.759700 10.3291982 10.55156119 10.5187426
cvpred 10.5461399 10.59924311 10.751905 10.3195768 10.54693382 10.5105774
LNMEDHVAL 10.6712783 10.51596683 10.463103 9.9850675 10.49681440 10.1924188
CV residual 0.1251384 -0.08327628 -0.288802 -0.3345092 -0.05011942 -0.3181585
[,197] [,198] [,199] [,200] [,201] [,202]
Predicted 10.8256776 10.640402 12.125898 10.3464894 11.19229398 11.11985581
cvpred 10.8159686 10.632173 12.108707 10.3307828 11.18299996 11.11064598
LNMEDHVAL 9.9664624 10.419301 11.793583 10.9560559 11.12873249 11.12431747
CV residual -0.8495063 -0.212872 -0.315124 0.6252731 -0.05426747 0.01367149
[,203] [,204] [,205] [,206] [,207] [,208]
Predicted 11.1702176 11.24766586 10.9416272 10.9679949 11.0169074 11.4343347
cvpred 11.1629698 11.23781388 10.9333999 10.9547467 11.0091624 11.4227373
LNMEDHVAL 11.2050407 11.27212698 11.2606105 11.1533893 11.3337988 11.2064003
CV residual 0.0420709 0.03431309 0.3272107 0.1986426 0.3246364 -0.2163369
[,209] [,210] [,211] [,212] [,213] [,214]
Predicted 10.902141 11.33488126 11.5531416 11.21614512 11.84332872 11.3008000
cvpred 10.894483 11.32205826 11.5399562 11.20844909 11.82734472 11.2890605
LNMEDHVAL 11.242428 11.28099341 11.6377944 11.15625052 11.88724384 11.6333716
CV residual 0.347945 -0.04106486 0.0978382 -0.05219857 0.05989913 0.3443111
[,215] [,216] [,217] [,218] [,219] [,220]
Predicted 11.3651365 11.2139411 11.5695780 10.7403984 10.9584156 10.4970844
cvpred 11.3532833 11.2062666 11.5559916 10.7340741 10.9500127 10.4882388
LNMEDHVAL 11.6118654 11.7035458 11.9349199 11.7035458 11.3667430 11.0153451
CV residual 0.2585822 0.4972792 0.3789283 0.9694717 0.4167303 0.5271062
[,221] [,222] [,223] [,224] [,225] [,226]
Predicted 10.9730394 10.6983766 10.70479247 10.42319344 10.699740 10.6558323
cvpred 10.9647329 10.6898469 10.69472902 10.41286115 10.692238 10.6462214
LNMEDHVAL 11.3725133 10.9920495 10.61643736 10.43705266 10.545341 10.3920676
CV residual 0.4077804 0.3022026 -0.07829166 0.02419151 -0.146897 -0.2541538
[,227] [,228] [,229] [,230] [,231] [,232]
Predicted 10.8791192 11.61527658 10.76657276 10.7219291 11.6716961 11.1859184
cvpred 10.8747124 11.60246640 10.75617632 10.7141081 11.6592486 11.1775901
LNMEDHVAL 11.4349639 11.53468696 10.71219307 10.9886768 11.4957793 11.3337988
CV residual 0.5602515 -0.06777944 -0.04398324 0.2745688 -0.1634693 0.1562087
[,233] [,234] [,235] [,236] [,237] [,238]
Predicted 11.12124639 11.4565950 11.4389361 11.23737945 11.2762058 11.3802500
cvpred 11.11447653 11.4457980 11.4273275 11.22770418 11.2659122 11.3709524
LNMEDHVAL 11.07751648 11.2131708 11.1619485 11.17324810 11.1272630 11.2036792
CV residual -0.03696005 -0.2326271 -0.2653789 -0.05445608 -0.1386492 -0.1672732
[,239] [,240] [,241] [,242] [,243] [,244]
Predicted 10.8945948 10.9899115 11.06894171 11.0251804 11.0843130 10.9601833
cvpred 10.8855631 10.9806437 11.06102105 11.0158900 11.0750557 10.9513905
LNMEDHVAL 11.0037651 11.4647851 11.14475614 10.7954856 10.8257604 10.8336812
CV residual 0.1182021 0.4841414 0.08373509 -0.2204044 -0.2492953 -0.1177093
[,245] [,246] [,247] [,248] [,249]
Predicted 10.7882361 11.0206216 11.003635285 10.8628335 10.42336948
cvpred 10.7785685 11.0114254 10.994401815 10.8565122 10.41416986
LNMEDHVAL 10.9059560 10.8780472 10.988676821 11.0219025 10.43998092
CV residual 0.1273875 -0.1333782 -0.005724994 0.1653903 0.02581106
[,250] [,251] [,252] [,253] [,254] [,255]
Predicted 11.0143475 10.7987867 10.618356 9.924930 10.60968873 10.71749197
cvpred 11.0053289 10.7920761 10.612332 9.907239 10.59821598 10.70499707
LNMEDHVAL 10.6964801 10.3703613 9.971146 10.976782 10.68281243 10.74505474
CV residual -0.3088488 -0.4217148 -0.641186 1.069543 0.08459645 0.04005766
[,256] [,257] [,258] [,259] [,260] [,261]
Predicted 10.84663824 10.9742000 10.7806979 10.8741441 10.71430 10.9893040
cvpred 10.83939843 10.9665487 10.7751894 10.8663509 10.70743 10.9814673
LNMEDHVAL 10.77895629 10.7472076 10.8799322 10.6261935 10.54797 10.6065851
CV residual -0.06044214 -0.2193411 0.1047428 -0.2401573 -0.15946 -0.3748822
[,262] [,263] [,264] [,265] [,266] [,267]
Predicted 10.5954581 10.9678934 10.9363545 10.76301537 11.152528 11.3849729
cvpred 10.5882992 10.9607852 10.9289845 10.75602422 11.144493 11.3756292
LNMEDHVAL 10.3089527 10.7166375 10.5815211 10.68738910 10.964744 10.9987609
CV residual -0.2793465 -0.2441477 -0.3474634 -0.06863512 -0.179749 -0.3768683
[,268] [,269] [,270] [,271] [,272] [,273]
Predicted 11.0641773 11.1898949 11.21671863 10.8648777 10.3290299 10.51287716
cvpred 11.0563696 11.1804104 11.20644472 10.8566229 10.3200481 10.50497102
LNMEDHVAL 10.9348911 10.7557730 11.27339843 10.6213273 10.6016223 10.52942598
CV residual -0.1214785 -0.4246374 0.06695371 -0.2352955 0.2815741 0.02445497
[,274] [,275] [,276] [,277] [,278] [,279]
Predicted 10.8411304 11.1506543 11.0387061 10.956871 10.7954776 10.639018
cvpred 10.8332455 11.1435974 11.0315087 10.948678 10.7886606 10.631663
LNMEDHVAL 10.9784900 10.5320962 10.8277465 10.654904 10.6041067 10.918718
CV residual 0.1452444 -0.6115012 -0.2037622 -0.293774 -0.1845538 0.287055
[,280] [,281] [,282] [,283] [,284] [,285]
Predicted 10.94864513 11.2503378 10.89094696 11.129783 11.02396198 11.1996022
cvpred 10.93794988 11.2395371 10.88269587 11.121167 11.01541800 11.1900452
LNMEDHVAL 10.86666187 10.9508065 10.80567936 10.881814 10.97507117 11.3132543
CV residual -0.07128801 -0.2887306 -0.07701651 -0.239353 -0.04034683 0.1232091
[,286] [,287] [,288] [,289] [,290]
Predicted 11.141649300 11.27760238 11.0898505 11.24294562 11.713582
cvpred 11.134680323 11.26470000 11.0813159 11.23244649 11.701031
LNMEDHVAL 11.133128104 11.31691058 11.2872788 11.32900263 11.352757
CV residual -0.001552219 0.05221058 0.2059629 0.09655614 -0.348274
[,291] [,292] [,293] [,294] [,295] [,296]
Predicted 11.2968716 11.3116928 11.5581737 10.97812465 11.0790972 10.94900689
cvpred 11.2868241 11.3014630 11.5451672 10.96863217 11.0727387 10.94188644
LNMEDHVAL 11.1154285 11.5297826 11.3445068 10.92233487 11.1968439 10.99541085
CV residual -0.1713956 0.2283195 -0.2006603 -0.04629729 0.1241053 0.05352441
[,297] [,298] [,299] [,300] [,301]
Predicted 10.97982613 11.3441720 11.23966780 11.1562168 11.34856305
cvpred 10.97141133 11.3334821 11.23098812 11.1491057 11.33837014
LNMEDHVAL 11.03327546 11.2198958 11.19958365 10.9699209 11.27085390
CV residual 0.06186413 -0.1135863 -0.03140448 -0.1791847 -0.06751624
[,302] [,303] [,304] [,305] [,306]
Predicted 11.08068388 10.92401919 11.09701977 11.06483214 11.06885192
cvpred 11.07327877 10.91778138 11.08825063 11.05673661 11.06028768
LNMEDHVAL 11.15482093 10.87047140 11.07596969 10.95954023 10.96992094
CV residual 0.08154215 -0.04730998 -0.01228094 -0.09719638 -0.09036673
[,307] [,308] [,309] [,310] [,311] [,312]
Predicted 10.6403949 10.94502 10.89099264 10.78293153 11.0119061 10.9324385
cvpred 10.6337457 10.93739 10.88190467 10.77666325 11.0062034 10.9196060
LNMEDHVAL 10.8257604 10.84739 10.92773543 10.79957558 11.2398035 11.0365013
CV residual 0.1920146 -0.09000 0.04583076 0.02291232 0.2336002 0.1168953
[,313] [,314] [,315] [,316] [,317] [,318]
Predicted 10.6999495 10.920559 11.08535172 10.94854422 10.8249527 10.93634007
cvpred 10.6894018 10.912043 11.07673512 10.94027025 10.8188899 10.92660897
LNMEDHVAL 10.8799322 10.768485 11.02679245 10.95605590 10.9937316 10.82972862
CV residual 0.1905304 -0.143558 -0.04994267 0.01578565 0.1748417 -0.09688035
[,319] [,320] [,321] [,322] [,323] [,324]
Predicted 11.1790570 10.8919180 11.124153320 10.98995 10.8556456 11.0304640
cvpred 11.1701043 10.8839508 11.116161377 10.98045 10.8497557 11.0226171
LNMEDHVAL 10.8761586 11.0759697 11.122841459 11.32176 11.4175153 11.3361883
CV residual -0.2939457 0.1920189 0.006680082 0.34131 0.5677596 0.3135712
[,325] [,326] [,327] [,328] [,329] [,330]
Predicted 10.8499114 10.9840833 11.0015770 11.041179 11.2235979 11.3038996
cvpred 10.8443705 10.9761859 10.9944012 11.031911 11.2147447 11.2941898
LNMEDHVAL 11.4240943 11.3621026 11.3278000 11.683512 11.5366420 11.6369114
CV residual 0.5797237 0.3859167 0.3333988 0.651601 0.3218972 0.3427216
[,331] [,332] [,333] [,334] [,335] [,336]
Predicted 11.42506643 12.2274488 10.9928030 10.8530483 11.37148704 11.0741958
cvpred 11.41447650 12.2096147 10.9857110 10.8473553 11.36158098 11.0657655
LNMEDHVAL 11.50791292 12.0441418 11.4584693 11.4647851 11.29352490 11.3265959
CV residual 0.09343642 -0.1654729 0.4727582 0.6174297 -0.06805608 0.2608304
[,337] [,338] [,339] [,340] [,341] [,342]
Predicted 11.2892248 11.18774 10.9666797 11.027649 11.209920 11.5802348
cvpred 11.2804489 11.17868 10.9601662 11.020075 11.201803 11.5684238
LNMEDHVAL 11.5287988 11.45952 11.6045927 11.524854 11.661345 11.3736634
CV residual 0.2483499 0.28084 0.6444264 0.504779 0.459542 -0.1947604
[,343] [,344]
Predicted 11.385843 11.8114077
cvpred 11.375951 11.7970672
LNMEDHVAL 11.491702 11.4637352
CV residual 0.115751 -0.3333319
Sum of squares = 76.8 Mean square = 0.22 n = 344
Overall (Sum over all 344 folds)
ms
0.1960024 [1] 0.44272164. DISCUSSION AND LIMITATIONS
- INSTRUCTIONS: Recap what you did in the paper and your findings. Discuss what conclusions you can draw, which variables were significant and whether that was surprising or not.
- INSTRUCTIONS: Talk about the quality of the model – that is, state if this is a good model overall (e.g., R2, F-ratio test), and what other predictors that we didn’t include in our model might be associated with our dependent variable.
- Looking at the stepwise regression results, did the final model include all 4 predictors or were some dropped? What does that tell you about the quality of the model?
- Looking at the cross-validation results, was the RMSE better for the 4 predictor model or the 2 predictor model?
- INSTRUCTIONS: If you haven’t done that in the Results section, talk explicitly about the limitations of the model – that is, mention which assumptions were violated, and if applicable, how that may affect the model/parameter estimation/estimated significance.
- In addition, talk about the limitations of using the NBELPOV100 variable as a predictor – that is, what are some limitations of using the raw number of households living in poverty rather than a percentage?
- INSTRUCTIONS: Would it make sense to run Ridge or LASSO regression here? Explain briefly (~4-5 sentences) what these methods are, when they’re used, and why they would or would not be appropriate here.