gausscov (version 0.1.4)

f3sti: Selection of covariates with given excluded covariates

Description

Selection of covariates with given excluded covariates

Usage

f3sti(y,x,covch,ind,m,kexmx=100,p0=0.01,nu=1,kmn=0,kmx=0,
 mx=21,kex=0,sub=T,inr=T,xinr=F,qq=0)

Arguments

y

Dependent variable

x

Covariates

covch

Sum of squared residuals and selected covariates

ind

The excluded covariates

m

Number of iterations

kexmx

The maximum number of excluded covariates

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

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

ind1 The excluded covariates covch The sum of squared residuals and the selected covariates ordered in increasing size of sum of squared residuals

Examples

# NOT RUN {
data(leukemia_y)
data(leukemia_x)
covch=c(2.023725,1182,1219,2888,0)
ind<-c(1182,1219,2888,0,0,0,0,0,0)
ind<-matrix(ind,ncol=3)
m<-3
a<-f3sti(ly.original,lx.original,covch,ind,m)
# }