mixgamma: Gamma mixture

In anapuce: Tools for Microarray Data Analysis

Description

This function provides an estimation of a mixture of gamma distributions. The code is inspired from the varmixt package.

Usage

mixgamma(VAR, dfreedom, var.init, pi.init, nmixt, stop.crit, display = TRUE,
         niter.max = 50000, criterion = criterion)

Arguments

VAR	vector of estimated variance.
dfreedom	degrees of freedom of the estimated variance.
var.init	vector of initial variances for the mixture.
pi.init	vector of initial prior probability for the mixture.
nmixt	integer : number of components in the mixture model.
stop.crit	the stopping relative precision limit for stopping EM algorithm.
display	boolean : should the result of model fitting be displayed on the screen ?
niter.max	integer : maximum number of iterations of the EM algorithm.
criterion	criterion for the convergence of the EM algorithm : either "likelihood" for criterion base on loglikelihood either "parameter".

Value

a LIST with the following components :

BIC.crit	value of the BIC criterion
p.i	the probability of each variance component
vars	variances
loglike	value of the criterion base on Loglikelihood
nmixt	number of variance components
tau	the matrix of posterior probability that a gene belongs to each variance component. One row per gene, one column per variance component.
VM2	the variance attributed to each gene according to the MAP rule - Delmar et al. (2005) JRSS
VM	the variance attributed to each gene taking into account the tau values - Delmar et al. (2005) Bioinformatics

Author(s)

P. Delmar and M.-L. Martin-Magniette

See Also

est.varmixt

anapuce documentation built on May 2, 2019, 9:44 a.m.