| cv.lm {DAAG} | R Documentation |
Cross-Validation for Linear Regression
Description
This function gives internal and cross-validation measures of predictive accuracy for ordinary linear regression. 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 |
form.lm |
a formula object |
m |
the number of folds |
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
ss |
the cross-validation residual sum of squares |
df |
degrees of freedom |
Author(s)
J.H. Maindonald
See Also
lm
Examples
cv.lm()