dist.Multivariate.Polya: Multivariate Polya Distribution

Description Usage Arguments Details Value Author(s) See Also Examples

Description

These functions provide the density and random number generation for the multivariate Polya distribution.

Usage

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dmvpolya(x, alpha, log=FALSE)
rmvpolya(n, alpha)

Arguments

x

This is data or parameters in the form of a vector of length k.

n

This is the number of random draws to take from the distribution.

alpha

This is shape vector alpha with length k.

log

Logical. If log=TRUE, then the logarithm of the density is returned.

Details

The multivariate Polya distribution is named after George Polya (1887-1985). It is also called the Dirichlet compound multinomial distribution or the Dirichlet-multinomial distribution. The multivariate Polya distribution is a compound probability distribution, where a probability vector p is drawn from a Dirichlet distribution with parameter vector alpha, and a set of N discrete samples is drawn from the categorical distribution with probability vector p and having K discrete categories. The compounding corresponds to a Polya urn scheme. In document classification, for example, the distribution is used to represent probabilities over word counts for different document types. The multivariate Polya distribution is a multivariate extension of the univariate Beta-binomial distribution.

Value

dmvpolya gives the density and rmvpolya generates random deviates.

Author(s)

Statisticat, LLC [email protected]

See Also

dcat, ddirichlet, and dmultinom.

Examples

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library(LaplacesDemon)
dmvpolya(x=1:3, alpha=1:3, log=TRUE)
x <- rmvpolya(1000, c(0.1,0.3,0.6))

LaplacesDemon documentation built on May 29, 2017, 11:54 p.m.