rcat function

Random generation for categorical distribution

Random generation for categorical distribution

Draw random samples from a categorical distribution given a matrix of probabilities. rcat is vectorized and written in C++ for speed.

rcat(n, prob)

Arguments

  • n: Number of random observations to draw.
  • prob: A matrix of probabilities where rows correspond to observations and columns correspond to categories.

Returns

A vector of random samples from the categorical distribution. The length of the sample is determined by n. The numerical arguments other than n are recycled so that the number of samples is equal to n.

Examples

p <- c(.2, .5, .3) n <- 10000 pmat <- matrix(rep(p, n), nrow = n, ncol = length(p), byrow = TRUE) # rcat set.seed(100) ptm <- proc.time() samp1 <- rcat(n, pmat) proc.time() - ptm prop.table(table(samp1)) # rmultinom from base R set.seed(100) ptm <- proc.time() samp2 <- t(apply(pmat, 1, rmultinom, n = 1, size = 1)) samp2 <- apply(samp2, 1, function(x) which(x == 1)) proc.time() - ptm prop.table(table(samp2))