Multinomial: Multinomial distribution
In extraDistr: Additional Univariate and Multivariate Distributions

Description Usage Arguments Details References See Also Examples

Probability mass function and random generation for the multinomial distribution.

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dmnom(x, size, prob, log = FALSE)

rmnom(n, size, prob)

`x`	k-column matrix of quantiles.
`size`	numeric vector; number of trials (zero or more).
`prob`	k-column numeric matrix; probability of success on each trial.
`log`	logical; if TRUE, probabilities p are given as log(p).
`n`	number of observations. If `length(n) > 1`, the length is taken to be the number required.

Probability mass function

f(x) = n!/prod(x[i]!) * prod(p[i]^x[i])

Gentle, J.E. (2006). Random number generation and Monte Carlo methods. Springer.

Binomial, Multinomial

# Generating 10 random draws from multinomial distribution
# parametrized using a vector

(x <- rmnom(10, 3, c(1/3, 1/3, 1/3)))

# Results are consistent with dmultinom() from stats:

all.equal(dmultinom(x[1,], 3, c(1/3, 1/3, 1/3)),
          dmnom(x[1, , drop = FALSE], 3, c(1/3, 1/3, 1/3)))