f2st {gausscov}

Repeated stepwise selection of covariates

Description

Repeated stepwise selection of covariates

Usage

f2st(y,x,p0=0.01,kmn=0,kmx=0,kex=0,mx=21,lm=9^9,sub=T,inr=T,xinr=F,qq=-1)

Arguments

y

Dependent variable

x

Covariates

p0

The P-value cut-off

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.

kex

The excluded covariates

mx

The maximum number of covariates for an all subset search

lm

The maximum number of linear approximations

sub

Logical if TRUE select the best subset

inr

Logical if TRUE include an intercept

xinr

Logical if TRUE intercept already included

qq

The number of covariates to choose from. If qq=-1 the number of covariates of x is used.

Value

pv In order the linear approximation, the included covariates, the Gaussian P-values.

Examples

data(boston)
bostint<-fgeninter(boston[,1:13],2)[[1]]
a<-f2st(boston[,14],bostint,lm=3,sub=FALSE)