bestModel_mu: Selecting the best model, by bootstrap and Cross Validation,...

In cdv04/ACTR:

Description

6 linear models are compared using Cross Validation on the basis of the least error of prediction

Usage

bestModel_mu(errMod_Mu.list)

Arguments

errMod_Mu.list

A list containing the error of prediction of wMuC_lg for each model and each bootstrap samples

Details

The 6 linear models are :

mod1 : wMuC_lg ~ 1

mod2 : wMuC_lg ~ wMuA_lg

mod3 : wMuC_lg ~ wMuA_lg + wSigmaA_lg

mod4 : wMuC_lg ~ wMuA_lg + I(wMuA_lg^2)

mod5 : wMuC_lg ~ wMuA_lg + I(wMuA_lg^2) + wSigmaA_lg

mod6 : wMuC_lg ~ wMuA_lg + I(wMuA_lg^2) + wSigmaA_lg + I(wSigmaA_lg^2)

Value

The function return the formula of the best selected model

Examples

data(cipr)
ciprKP <- subset_data(cipr, Class,6)
PAC.bt <- lapply(ciprKP.bt,est_PAC,Class)
errMod_mu <- lapply(PAC.bt,msep_mu)
errMod_sigma <- lapply(PAC.bt,msep_sigma)
bm_mu <- bestModel_mu(errMod_mu)

cdv04/ACTR documentation built on May 13, 2019, 2:42 p.m.