rDirichlet

dDirichlet

Functions to compute the density of a Dirichlet distribution and to generate random realizations from such a distribution.

Dirichlet

A Bayesian clustering method for replicated time series or replicated measurements from multiple experimental conditions, e.g., time-course gene expression data. It estimates the number of clusters directly from the data using a Dirichlet-process prior. See Fu, A. Q., Russell, S., Bray, S. and Tavare, S. (2013) Bayesian clustering of replicated time-course gene expression data with weak signals. The Annals of Applied Statistics. 7(3) 1334-1361. <doi:10.1214/13-AOAS650>.

Audrey Q Fu

DIRECT

Bayesian Clustering of Multivariate Data Under the
Dirichlet-Process Prior

Dirichlet function

<dl> <dt>alpha</dt>
<dd>Shape parameter vector.</dd> <dt>x</dt>
<dd>Vector of the same length as <code>alpha</code>.</dd> <dt>n</dt>
<dd>Number of realizations (vectors) to generate.</dd> <dt>log</dt>
<dd>Logical value. TRUE if computing the log density. Default is FALSE.</dd></dl>

Arguments

Audrey Q. Fu coded <code>dDirichlet</code>.
The code for <code>rDirichlet</code> is taken from a similar function in R package <code>gregmisc</code> by Gregory R. Warnes. His code was based on code posted by Ben Bolker to R-News on 15 Dec 2000. See documentation in gregmisc for further information.

Author

The Dirichlet Distribution — Dirichlet

<dl>

 <dt>alpha</dt>
<dd>Shape parameter vector.</dd>

 <dt>x</dt>
<dd>Vector of the same length as <code>alpha</code>.</dd>

 <dt>n</dt>
<dd>Number of realizations (vectors) to generate.</dd>

 <dt>log</dt>
<dd>Logical value. TRUE if computing the log density. Default is FALSE.</dd>

</dl>

Dirichlet: The Dirichlet Distribution

Description

Usage

Value

Arguments

Author

Examples