ml.quantile_f: SLMix packageml.quantile.f

In alexpkeil1/SLmix: Extensions of Bayesian Kernel Machine Regression and Weighted Quantile Sums for prediction and integration with SuperLearner package

Usage

ml.quantile_f(data, v_n, breaks)

Arguments

data
v_n
breaks

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (data, v_n, breaks) 
{
    for (i in 1:length(v_n)) {
        dat_num = as.numeric(unlist(data[, v_n[i]]))
        data[[paste(v_n[i], "q", sep = "_")]] = cut(dat_num, 
            breaks = breaks[, i], labels = FALSE, include.lowest = TRUE) - 
            1
    }
    return(data)
  }

alexpkeil1/SLmix documentation built on Aug. 15, 2020, 9:10 a.m.