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## File Name: regpolca_postproc_count_regularized_parameters.R
## File Version: 0.292
regpolca_postproc_count_regularized_parameters <- function(item, set_equal,
lca_dich, probs_items, nclasses, ncats)
{
item1_index <- NULL
n_reg <- 0
if (lca_dich){
ind <- c(1)
item1 <- item[,-ind]
TP <- ncol(item1)
I <- nrow(item)
item1_index <- 0*item1
for (ii in 1:I){
index_ii <- item1_index[ii,]
item_ii <- item1[ii,]
NC <- length(item_ii)
index_ii <- 1:NC
for (aa in 1:(NC-1)){
val_aa <- item_ii[aa]
for (bb in (aa+1):NC){
val_bb <- item_ii[bb]
if (abs(val_aa-val_bb)<set_equal){
index_ii[bb] <- index_ii[aa]
}
}
}
ind_ii <- match( index_ii, unique(index_ii) )
item1_index[ii,] <- ind_ii
w1 <- t(item_ii)
a1 <- stats::aggregate(w1[,1], list(ind_ii), mean)
probs_mod <- a1[ind_ii,2]
item[ii, -ind] <- probs_mod
probs_items[ii,2,] <- probs_mod
probs_items[ii,1,] <- 1 - probs_mod
} # end ii
H <- I*TP
n_reg <- H - sum( apply(item1_index, 1, max))
}
if ((! lca_dich) & (set_equal>0)){
items <- unique(paste(item$item))
I <- length(items)
n_reg <- 0
lem1 <- c(1,2)
for (ii in 1:I){
item_ii <- items[ii]
ind_ii <- which( item[,'item']==item_ii )
item_tab_ii <- item[ind_ii,-lem1]
item_tab_ii[-c(ind_ii[1]),] <-
set_equal*round( item_tab_ii[-c(ind_ii[1]),] / set_equal, 0)
item_tab_ii[1,] <- 1 - colSums(item_tab_ii[-1,])
item[ind_ii, -c(lem1) ] <- item_tab_ii
LU <- length( unique( unlist(item_tab_ii[-1,] )))
H <- (nrow(item_tab_ii)-1)*ncol(item_tab_ii)
n_reg <- n_reg + H - LU
for (hh in 1:ncats[ii]){
v1 <- as.numeric(item_tab_ii[hh,])
probs_items[ii,hh,] <- v1
}
}
}
res <- list(item1_index=item1_index, n_reg=n_reg, item=item,
probs_items=probs_items)
return(res)
}
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