ran_beta_binom: Beta-Binomial Random Samples

In extras: Helper Functions for Bayesian Analyses

Beta-Binomial Random Samples

Description

This parameterization of the beta-binomial distribution uses an expected probability parameter, prob, and a dispersion parameter, theta. The parameters of the underlying beta mixture are alpha = (2 * prob) / theta and beta = (2 * (1 - prob)) / theta. This parameterization of theta is unconventional, but has useful properties when modelling. When theta = 0, the beta-binomial reverts to the binomial distribution. When theta = 1 and prob = 0.5, the parameters of the beta distribution become alpha = 1 and beta = 1, which correspond to a uniform distribution for the beta-binomial probability parameter.

Usage

ran_beta_binom(n = 1, size = 1, prob = 0.5, theta = 0)

Arguments

n	A non-negative whole number of the number of random samples to generate.
size	A non-negative whole numeric vector of the number of trials.
prob	A numeric vector of values between 0 and 1 of the probability of success.
theta	A non-negative numeric vector of the dispersion for the mixture models (student, gamma-Poisson and beta-binomial).

Value

A numeric vector of the random samples.

See Also

Other ran_dist: ran_bern(), ran_binom(), ran_gamma(), ran_gamma_pois(), ran_gamma_pois_zi(), ran_lnorm(), ran_neg_binom(), ran_norm(), ran_pois(), ran_pois_zi(), ran_skewnorm(), ran_student()

Examples

ran_beta_binom(10, 1, 0.5, 0)

extras documentation built on April 4, 2025, 2:40 a.m.