Generate Random Draws from a Discrete Set of Labels with Associated Probabilities

Allows different class probabilities for each person by supplying a matrix with one column for each class and one row for each person.

Usage

rcategorical(n, probs, labels=NULL, output="numeric",
             reference=NULL)

Arguments

n: How many draws to make. Passed to the size argument of the sample function if probs is not a matrix.
probs: Either a numeric vector of probabilities which sums to one or a matrix with one column for each desired class and n rows. Passed to the probs argument of the sample function if a numeric vector is passed.
labels: A vector of labels to draw from. If NULL (default), it simply uses integers starting from 1. Passed to the x argument of the sample function if probs is not a matrix.
output: A single character string specifying the output format of the results. Must be either "numeric" (default), "character" or "factor". If labels are supplied, the output will be parsed as characters by default.
reference: A single character string, specifying which of the possible values should be considered the reference when output="factor" (ignored otherwise).

Details

In case of a simple numeric vector (class probabilities should be the same for all draws), this function is only a wrapper for the sample function, to make the code more consistent. It uses weighted sampling with replacement. Otherwise, custom code is used which is faster than the standard rmultinom function.

Author

Robin Denz

Value

Returns a numeric vector (or factor vector if coerce2factor=TRUE) of length n.

Examples

library(simDAG)

rcategorical(n=5, labels=c("A", "B", "C"), probs=c(0.1, 0.2, 0.7))
#> [1] "C" "C" "C" "A" "C"

rcategorical(n=2, probs=matrix(c(0.1, 0.2, 0.5, 0.7, 0.4, 0.1), nrow=2))
#> [1] 1 2