Given the individual component likelihoods for a mixture model, estimates the mixture proportions.
mixIP(matrix_lik, prior, pi_init = NULL, control = list(), weights = NULL)A list, including the estimates (pihat), the log likelihood for each interation (B) and a flag to indicate convergence
a n by k matrix with (j,k)th element equal to \(f_k(x_j)\).
a k vector of the parameters of the Dirichlet prior on \(\pi\). Recommended to be rep(1,k)
the initial value of \(\pi\) to use. If not specified defaults to (1/k,...,1/k).
A list of control parameters to be passed to REBayes::KWDual
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.