w_mixEM {ashr} | R Documentation |
Given the individual component likelihoods for a mixture model, and a set of weights, estimates the mixture proportions by an EM algorithm.
w_mixEM(matrix_lik, prior, pi_init = NULL, weights = NULL, control = list())
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). |
weights, |
an n vector of weights |
control |
A list of control parameters for the SQUAREM algorithm, default value is set to be control.default=list(K = 1, method=3, square=TRUE, step.min0=1, step.max0=1, mstep=4, kr=1, objfn.inc=1,tol=1.e-07, maxiter=5000, trace=FALSE). |
Fits a k component mixture model
f(x|π)= ∑_k π_k f_k(x)
to independent and identically distributed data x_1,…,x_n with weights w_1,…,w_n. Estimates mixture proportions π by maximum likelihood, or by maximum a posteriori (MAP) estimation for a Dirichlet prior on π (if a prior is specified). Here the log-likelihood for the weighted data is defined as l(π) = ∑_j w_j log f(x_j | π). Uses the SQUAREM package to accelerate convergence of EM. 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