| f3sti {gausscov} | R Documentation |
Selection of covariates with given excluded covariates
Description
Selection of covariates with given excluded covariates
Usage
f3sti(y,x,covch,ind,m,p0=0.01,kmn=0,kmx=0, kex=0,mx=21,sub=T,inr=F,xinr=F,qq=-1,kexmx=100)
Arguments
y |
Dependent variable |
x |
Covariates |
covch |
Sum of squared residuals and selected covariates |
ind |
The excluded covariates |
m |
Number of iterations |
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 covariates for an all subset search |
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=-1 the number of covariates of x is used. |
kexmx |
The maximum number of covariates in an approximation. |
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
data(leukemia)
covch=c(2.023725,1182,1219,2888,0)
covch<-matrix(covch,nrow=1,ncol=5)
ind<-c(1182,1219,2888)
ind<-matrix(ind,nrow=3,ncol=1)
m<-1
a<-f3sti(leukemia[[1]],leukemia[[2]],covch,ind,m,kexmx=5)