Multinomial

0th

Percentile

Multinomial distribution

Probability mass function and random generation for the multinomial distribution.

Keywords
distribution
Usage
dmnom(x, size, prob, log = FALSE)

rmnom(n, size, prob)

Arguments
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.

Details

Probability mass function $$ f(x) = \frac{n!}{\prod_{i=1}^k x_i} \prod_{i=1}^k p_i^{x_i} $$

References

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

See Also

Binomial, Multinomial

Aliases
  • Multinomial
  • dmnom
  • rmnom
Examples
# NOT RUN {
# 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)))

# }
Documentation reproduced from package extraDistr, version 1.9.1, License: GPL-2

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