cv.lm: Cross-Validation for Linear Regression
Description
This function gives internal and cross-validation measures of predictive
accuracy for simple linear regression. (For multiple linear
regression, CVlm should be used). The data are
randomly assigned to a number of `folds'.
Each fold is removed, in turn, while the remaining data is used
to re-fit the regression model and to predict at the deleted observations.Usage
cv.lm(df = houseprices, form.lm = formula(sale.price ~ area), m=3, dots =
FALSE, seed=29, plotit=TRUE, printit=TRUE)Arguments
df
a data frame in which the first column holds the response
variable and the second column holds the predictor
dots
uses pch=16 for the plotting character
seed
random number generator seed
plotit
if TRUE, a plot is constructed on the active device
printit
if TRUE, output is printed to the screen
Value
- ssthe cross-validation residual sum of squares
- dfdegrees of freedom