betabinom: Beta-binomial distribution

In pomp: Statistical Inference for Partially Observed Markov Processes

Beta-binomial distribution

Description

Density and random generation for the Beta-binomial distribution with parameters size, mu, and theta.

Usage

rbetabinom(n = 1, size, prob, theta)

dbetabinom(x, size, prob, theta, log = FALSE)

Arguments

n	integer; number of random variates to generate.
size	size parameter of the binomial distribution
prob	mean of the Beta distribution
theta	Beta distribution dispersion parameter
x	vector of non-negative integer quantiles
log	logical; if TRUE, return logarithm(s) of probabilities.

Details

A variable X is Beta-binomially distributed if X\sim{\mathrm{Binomial}(n,P)} where P\sim{\mathrm{Beta}(\mu,\theta)}. Using the standard (a,b) parameterization, a=\mu\,\theta and b=(1-\mu)\,\theta.

Value

rbetabinom	Returns a vector of length n containing random variates drawn from the Beta-binomial distribution.
dbetabinom	Returns a vector (of length equal to the number of columns of x) containing the probabilities of observing each column of x given the specified parameters (size, prob, theta).

C API

An interface for C codes using these functions is provided by the package. Visit the package homepage to view the pomp C API document.

See Also

More on implementing POMP models: Csnippet, accumvars, basic_components, covariates, dinit_spec, dmeasure_spec, dprocess_spec, emeasure_spec, eulermultinom, parameter_trans(), pomp-package, pomp_constructor, prior_spec, rinit_spec, rmeasure_spec, rprocess_spec, skeleton_spec, transformations, userdata, vmeasure_spec

pomp documentation built on Sept. 13, 2024, 1:08 a.m.