fasb: Calculates all subsets where each included covariate is...

In gausscov: The Gaussian Covariate Method for Variable Selection

Calculates all subsets where each included covariate is significant.

Description

It sel =TRUE it calls fselect.R and removes all such subsets which are a subset of some other selected subset. The remaining ones are ordered according to the sum of squared residuals. Subsets can be decoded with decode.R.

Usage

fasb(y,x,p0=0.01,q=-1,ind=0,sel=T,inr=T,xinr=F)

Arguments

y	The dependent variable
x	The covariates
p0	Cut-off p-value for significance
q	The number of covariates from which to choose. Equals number of covariates minus length of ind if q=-1.
ind	The indices of a subset of covariates for which all subsets are to be considered
sel	If TRUE calls fselect.R to removes all subsets of chosen sets
inr	If TRUE to include intercept
xinr	If TRUE intercept already included

Value

nv Coded List of subsets with number of covariates and sum of squared residuals

Examples

data(redwine)
nvv<-fasb(redwine[,12],redwine[,1:11])

gausscov documentation built on Oct. 12, 2023, 1:06 a.m.