cv.lm {DAAG} | R Documentation |
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.
cv.lm(df = houseprices, form.lm = formula(sale.price ~ area), m=3, dots = FALSE, seed=29, plotit=TRUE, printit=TRUE)
df |
a data frame in which the first column holds the response variable and the second column holds the predictor |
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 |
ss |
the cross-validation residual sum of squares |
df |
degrees of freedom |
J.H. Maindonald
CVlm
cv.lm()