R/modgen.R

In musto101/wilcox_R: What the package does (short line)

modgen <-
function(p,adz=FALSE){
#
# Used by regpre to generate all models
# p=number of predictors
# adz=T, will add the model where only a measure
# of location is used.
#
#
model<-list()
if(p>5)stop("Current version is limited to 5 predictors")
if(p==1)model[[1]]<-1
if(p==2){
model[[1]]<-1
model[[2]]<-2
model[[3]]<-c(1,2)
}
if(p==3){
for(i in 1:3)model[[i]]<-i
model[[4]]<-c(1,2)
model[[5]]<-c(1,3)
model[[6]]<-c(2,3)
model[[7]]<-c(1,2,3)
}
if(p==4){
for(i in 1:4)model[[i]]<-i
model[[5]]<-c(1,2)
model[[6]]<-c(1,3)
model[[7]]<-c(1,4)
model[[8]]<-c(2,3)
model[[9]]<-c(2,4)
model[[10]]<-c(3,4)
model[[11]]<-c(1,2,3)
model[[12]]<-c(1,2,4)
model[[13]]<-c(1,3,4)
model[[14]]<-c(2,3,4)
model[[15]]<-c(1,2,3,4)
}
if(p==5){
for(i in 1:5)model[[i]]<-i
model[[6]]<-c(1,2)
model[[7]]<-c(1,3)
model[[8]]<-c(1,4)
model[[9]]<-c(1,5)
model[[10]]<-c(2,3)
model[[11]]<-c(2,4)
model[[12]]<-c(2,5)
model[[13]]<-c(3,4)
model[[14]]<-c(3,5)
model[[15]]<-c(4,5)
model[[16]]<-c(1,2,3)
model[[17]]<-c(1,2,4)
model[[18]]<-c(1,2,5)
model[[19]]<-c(1,3,4)
model[[20]]<-c(1,3,5)
model[[21]]<-c(1,4,5)
model[[22]]<-c(2,3,4)
model[[23]]<-c(2,3,5)
model[[24]]<-c(2,4,5)
model[[25]]<-c(3,4,5)
model[[26]]<-c(1,2,3,4)
model[[27]]<-c(1,2,3,5)
model[[28]]<-c(1,2,4,5)
model[[29]]<-c(1,3,4,5)
model[[30]]<-c(2,3,4,5)
model[[31]]<-c(1,2,3,4,5)
}
if(adz){
ic<-length(model)+1
model[[ic]]<-0
}
model
}