DirichletDistribution {rdecision}

A parametrized Dirichlet distribution

Description

An R6 class representing a multivariate Dirichlet distribution.

Details

A multivariate Dirichlet distribution. See https://en.wikipedia.org/wiki/Dirichlet_distribution for details. Inherits from class Distribution.

Super class

rdecision::Distribution -> DirichletDistribution

Methods

Public methods

• DirichletDistribution$new()

• DirichletDistribution$distribution()

• DirichletDistribution$mean()

• DirichletDistribution$mode()

• DirichletDistribution$quantile()

• DirichletDistribution$varcov()

• DirichletDistribution$sample()

• DirichletDistribution$clone()

Inherited methods

• rdecision::Distribution$SD()
• rdecision::Distribution$order()
• rdecision::Distribution$r()

Method new()

Create an object of class DirichletDistribution.

Usage

DirichletDistribution$new(alpha)

Arguments

alpha

Parameters of the distribution; a vector of K numeric values each > 0, with K > 1.

Returns

An object of class DirichletDistribution.

Method distribution()

Accessor function for the name of the distribution.

Usage

DirichletDistribution$distribution()

Returns

Distribution name as character string.

Method mean()

Mean value of each dimension of the distribution.

Usage

DirichletDistribution$mean()

Returns

A numerical vector of length K.

Method mode()

Return the mode of the distribution.

Usage

DirichletDistribution$mode()

Details

Undefined if any alpha is \le 1.

Returns

Mode as a vector of length K.

Method quantile()

Quantiles of the univariate marginal distributions.

Usage

DirichletDistribution$quantile(probs)

Arguments

probs

Numeric vector of probabilities, each in range [0,1].

Details

The univariate marginal distributions of a Dirichlet distribution are Beta distributions. This function returns the quantiles of each marginal. Note that these are not the true quantiles of the multivariate Dirichlet.

Returns

A matrix of numeric values with the number of rows equal to the length of probs, the number of columns equal to the order; rows are labelled with quantiles and columns with the dimension (1, 2, etc).

Method varcov()

Variance-covariance matrix.

Usage

DirichletDistribution$varcov()

Returns

A positive definite symmetric matrix of size K by K.

Method sample()

Draw and hold a random sample from the distribution.

Usage

DirichletDistribution$sample(expected = FALSE)

Arguments

expected

If TRUE, sets the next value retrieved by a call to r() to be the mean of the distribution.

Returns

Void; sample is retrieved with call to r().

Method clone()

The objects of this class are cloneable with this method.

Usage

DirichletDistribution$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Author(s)

Andrew J. Sims [e-mail]