Determine the missclassification rate for a fitted model

Evaluate the misclassification rate, i.e. prediction error, for a fitted model on new data. To use as argument aggregation.fun in peperr call.

Usage

aggregation.misclass(full.data=NULL, response, x, model, cplx=NULL,  
type=c("apparent", "noinf"), fullsample.attr = NULL, ...)

full.data: passed from peperr, but not used for calculation of the misclassification rate.
response: vector of binary response.
x: n*p matrix of covariates.
model: model fitted with fit.fun.
cplx: passed from peperr, but not necessary for calculation of the misclassification rate.
type: character.
fullsample.attr: passed from peperr, but not necessary for calculation of the misclassification rate.
...: additional arguments, passed to predict function.

Misclassification rate is the ratio of observations for which prediction of response is wrong.

Scalar, indicating the misclassification rate.