# 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.

Binomial, Multinomial

• 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)))

# }