cv.binary {DAAG}R Documentation

Cross-Validation for Regression with a Binary Response

Description

This function gives internal and cross-validation measures of predictive accuracy for regression with a binary response. 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.binary(obj=frogs.glm, rand=NULL, nfolds=10, print.details=TRUE)

Arguments

obj a glm object
rand a vector which assigns each observation to a fold
nfolds the number of folds
print.details logical variable (TRUE = print detailed output, the default)

Value

the order in which folds were deleted
internal estimate of accuracy
cross-validation estimate of accuracy

Author(s)

J.H. Maindonald

See Also

glm

Examples

frogs.glm <- glm(pres.abs ~ log(distance) + log(NoOfPools), 
   family=binomial,data=frogs)
cv.binary(frogs.glm)
[Package DAAG version 0.76 Index]