categorizeMktQuantiles = function(jointDist, mkt, probs=NULL)
{
#library(data.table)
if(is.null(probs))
probs = seq(0,1,0.1)
# colN = colnames(dt)
#q = apply(jointDist[, mkt, drop=F], 2, FUN = function(c)return(quantile(c,probs)))
q = quantile(jointDist[, mkt, drop=F], probs)
#colnames(q) = mkts
#q_cats = replicate(n=length(mkt), expr = rep(NA_integer_, nrow(jointDist)))
q_cats = rep(NA_integer_, nrow(jointDist))
# colnames(q_cats ) = paste0(mkts, "_QUANTILES")
for(i in 1:(length(q)-1)){
if(i==1){
# q_cats[which(jointDist[, n] < q[i+1, n]), c(paste0(n, "_QUANTILES"))] = i
q_cats[which(jointDist[, mkt, drop=F] < q[i+1])] = i
} else if(i == (length(q)-1)){
# q_cats[which(jointDist[, n] >= q[i, n]), c(paste0(n, "_QUANTILES"))] = i
q_cats[which(jointDist[, mkt, drop=F] >= q[i])] = i
} else{
# q_cats[which((jointDist[, n] >= q[i, n]) & (jointDist[, n] < q[i+1, n])), c(paste0(n, "_QUANTILES"))] = i
q_cats[which((jointDist[, mkt, drop=F] >= q[i]) & (jointDist[, mkt, drop=F] < q[i+1]))] = i
}
}
return(q_cats)
}
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