cv.lm {DAAG}R Documentation

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

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

CVlm

Examples

cv.lm()

[Package DAAG version 1.12 Index]