msep_sigma: Estimating the Mean Squared Error of Prediction for Sigma...

Description Usage Arguments Details Value Examples

View source: R/msep_sigma.R

Description

6 linear models linear are compared using Cross Validation on the basis of the least error of prediction (cf Details)

Usage

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msep_sigma(PAC.df)

Arguments

PAC.df

A dataframe containing the weighted parameters in log10 scale (wMuA_lg, wMuC_lg, wSigmaA_lg, wSigmaC_lg)

Details

The 6 linear models are :

mod1 : wSigmaC_lg ~ 1

mod2 : wSigmaC_lg ~ wSigmaA_lg

mod3 : wMuC_lg ~ wMuA_lg + wSigmaA_lg

mod4 : wSigmaC_lg ~ wSigmaA_lg + I(wSigmaA_lg^2)

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

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

Value

The function return the formula of the best selected model

Examples

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library(ACTR)
ciprKP <- subset_data(cipr, Class,6)
PAC.bt <- lapply(ciprKP.bt,est_PAC,Class)
errMod_sigma <- lapply(PAC.bt,msep_sigma)

cdv04/ACTR documentation built on May 12, 2017, 1:15 a.m.