f3st: Stepwise selection of covariates

View source: R/f3st.R

f3stR Documentation

Stepwise selection of covariates

Description

Stepwise selection of covariates

Usage

f3st(y,x,m,kexmx=100,p0=0.01,nu=1,kmn=0,kmx=0,mx=21,lm=1000,kex=0,sub=T,inr=T,xinr=F,qq=0)

Arguments

y

Dependent variable

x

Covariates

m

The number of iterations

kexmx

The maximum number of covariates in an approximation

p0

The P-value cut-off

nu

The order statistic of Gaussian covariates used for comparison

kmn

The minimum number of included covariates irrespective of cut-off P-value

kmx

The maximum number of included covariates irrespective of cut-off P-value.

mx

The maximum number covariates for an all subset search

lm

The maximum number of approximations.

kex

The excluded covariates

sub

Logical if TRUE best subset selected

inr

Logical if TRUE include intercept if not present

xinr

Logical if TRUE intercept already present

qq

The number of covariates to choose from. If qq=0 the number of covariates of x is used.

Value

covch The sum of squared residuals and the selected covariates ordered in increasing size of sum of squared residuals.

lai The number of rows of covch

Examples

data(leukemia)
a<-f3st(leukemia[[1]],leukemia[[2]],m=2,kexmx=5,kmn=5,sub=TRUE)

gausscov documentation built on April 26, 2022, 5:07 p.m.

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