Nothing
fnextrm<-function(y,des,prvm) {
# get the variable names in the expanded data frame
nmsm<-colnames(des)
# eliminate the names already in the prvm
nmsm<-nmsm[!nmsm %in% prvm]
# get the length of the remaining vector of names
nmt<-length(nmsm)
pval<-rep(0,nmt)
# get the pvalue for the hierarchical model associated with each term in nmsm when
# combined with the prvm
for (i in 1:nmt) {
term<-nmsm[i]
#checks to see if term is an interaction or quadratic term
#gets first letter in term
t1<-substr(term,1,1)
t2<-substr(term,2,2)
t3<-substr(term,3,3)
iquad=FALSE
if(t1=="I"&& t2=="(") {iquad=TRUE}
hmt<-term
if(iquad){hmt<-c(term,t3)}
cmp<-FALSE
if(t2 != "" && iquad != TRUE){cmp=TRUE}
if(cmp){hmt<-c(t1,t3,term)}
hmt<-union(hmt,prvm)
d2<-data.frame(y=y,des[,hmt])
m2<-lm(y~(.),data=d2)
sm2<-summary(m2)
sm2f<-sm2$fstatistic
pval[i]<-1-pf(sm2f[1],sm2f[2],sm2f[3])
}
idx<-which.min(pval)
term<-nmsm[idx]
# gets hierarchical model for term whose hierarchical model has the smallest pvalue
#checks to see if term is an interaction or quadratic term
#gets first letter in term
t1<-substr(term,1,1)
t2<-substr(term,2,2)
t3<-substr(term,3,3)
iquad=FALSE
if(t1=="I"&& t2=="(") {iquad=TRUE}
mt<-term
if(iquad){mt<-c(term,t3)}
cmp<-FALSE
if(t2!= ""&&iquad!=TRUE){cmp=TRUE}
if(cmp){mt<-c(t1,t3,term)}
mt<-union(mt,prvm)
return(mt)
}
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