mixIP: Estimate mixture proportions of a mixture model by Interior...

In ashr: Methods for Adaptive Shrinkage, using Empirical Bayes

Estimate mixture proportions of a mixture model by Interior Point method

Description

Given the individual component likelihoods for a mixture model, estimates the mixture proportions.

Usage

mixIP(matrix_lik, prior, pi_init = NULL, control = list(), weights = NULL)

Arguments

matrix_lik,	a n by k matrix with (j,k)th element equal to f_k(x_j).
prior,	a k vector of the parameters of the Dirichlet prior on \pi. Recommended to be rep(1,k)
pi_init,	the initial value of \pi to use. If not specified defaults to (1/k,...,1/k).
control	A list of control parameters to be passed to REBayes::KWDual
weights	weights to be assigned to the observations (an n vector)

Details

Optimizes

L(pi)= sum_j w_j log(sum_k pi_k f_{jk}) + h(pi)

subject to pi_k non-negative and sum_k pi_k = 1. Here

h(pi)

is a penalty function h(pi) = sum_k (prior_k-1) log pi_k. Calls REBayes::KWDual in the REBayes package, which is in turn a wrapper to the mosek convex optimization software. So REBayes must be installed to use this. Used by the ash main function; there is no need for a user to call this function separately, but it is exported for convenience.

Value

A list, including the estimates (pihat), the log likelihood for each interation (B) and a flag to indicate convergence

ashr documentation built on Aug. 22, 2023, 1:07 a.m.