Nothing
#theta is only for labels here. It is unneeded
gen.rec.raw <- function(Pij, theta.names = NULL){
#matches results from R package classify wlord
nn <- dim(Pij)[1]
Pij[round(Pij,5)==1]<- 1-1e-4
Pij[round(Pij,5)==0]<- 1e-4
if(length(dim(Pij))==2){
ni <- dim(Pij)[2]
sc <- ni+1
Qjt <- 1-Pij
H <- apply(Qjt,1,prod)
Zjt <- Pij/Qjt
zm <- array(0, dim = c(nn, sc, ni))
zm[,1,] <- 1
zm[,2,1] <- Zjt[,1]
for(i in 2: ni){
for(s in 2:sc){
zm[,s,i] <- zm[,s,i-1] + Zjt[,i]*zm[,s-1,i-1]}}
out<- zm[,,ni]*H
rownames(out) <- theta.names
colnames(out) <- paste("x = " , 0:ni)
return(out)
}else{
nk <- dim(Pij)[2]
ni <- dim(Pij)[3]
zm <- array(0, dim = c(nn, nk*ni, ni))
zm[,1:nk,1] <- Pij[,,1]
for(i in 2:ni){
for(s in i:(i*nk)){
zm[ , s, i] <- rowSums(
as.matrix( zm[,s-1:(min(c(s-1, nk))),i-1] * Pij[,1:(min(c(s-1, nk))),i]))
}}
out<- zm[,ni:(nk*ni),ni]
rownames(out) <- theta.names
colnames(out) <-paste("x = " , 0:(((nk-1)*ni)))
return(out)}
}
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