FLAT_hda2 <-
function(mat, el = 1, metho = 0, p = 1.1,
method_mean_or_median = 1) {
if(dim(mat)[2] == 1){
d <- list(m = 0, n = 0, mat = mat, na_numbers = 0)
}
else{
bigindx <- rbind(seq_len(ncol(mat)));
colnames(bigindx) <- colnames(mat);
matt <- apply(bigindx, 2, function(j){
if(method_mean_or_median == 1){
f1prime(mat[, j], mat[, -(j)], eprime = el)}
else{f1prime3(mat[, j], mat[, -(j)], eprime = el)}
})
rownames(matt) <- rownames(mat)
m <- colSums(is.na(matt))
na_numbers <- as.matrix(
(rowSums(is.na(matt))) / dim(matt)[2])
n <- dim(matt)[1] - dim(matt[
rowSums(is.na(matt)) < p * dim(matt)[2], ])[1]
if(metho == 0){
mattt <- as.matrix(impute_median(matt[
rowSums(is.na(matt)) < p * dim(matt)[2], ],
apply(mat, 1, median)))
}else{
mattt <- as.matrix(impute_median(matt[
rowSums(is.na(matt)) < p * dim(matt)[2],],
metho))
}
d <- list(m = m, n = n, mat = mattt, na_numbers = na_numbers)
}
return(d)
}
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