mvnmixMaxPhiStep: mvnmixMaxPhiStep

Description Usage Arguments Value

Description

Given a pair of h and tau and data, compute ordinary & penalized log-likelihood ratio resulting from MEM algorithm at k=1,2,3, tailored for parallelization.

Usage

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mvnmixMaxPhiStep(htaupair, y, parlist, an, ninits, ninits.short, epsilon.short,
  epsilon, maxit.short, maxit, verb)

Arguments

htaupair

A set of h and tau

y

n by d matrix of data

parlist

The parameter estimates as a list containing alpha, mu, and sigma in the form of (alpha = (alpha_1,...,alpha_m), mu = (mu_1',...,mu_m'), sigma = (vech(sigma_1)',...,vech(sigma_m)')

an

a term used for penalty function

ninits

The number of randomly drawn initial values.

ninits.short

The number of candidates used to generate an initial phi, in short MEM

epsilon.short

The convergence criterion in short EM. Convergence is declared when the penalized log-likelihood increases by less than epsilon.short.

epsilon

The convergence criterion. Convergence is declared when the penalized log-likelihood increases by less than epsilon.

maxit.short

The maximum number of iterations in short EM.

maxit

The maximum number of iterations.

verb

Determines whether to print a message if an error occurs.

Value

A list of phi, log-likelihood, and penalized log-likelihood resulting from MEM algorithm.


kshimotsu/mvnMix documentation built on May 9, 2019, 5:50 a.m.