Estimate mixture proportions of a mixture model by Interior Point method
Given the individual component likelihoods for a mixture model, estimates the mixture proportions.
mixIP(matrix_lik, prior, pi_init = NULL, control = list(), weights = NULL)
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 π. Recommended to be rep(1,k) |
pi_init, |
the initial value of π 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) |
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.
A list, including the estimates (pihat), the log likelihood for each interation (B) and a flag to indicate convergence
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