% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ash.R
\name{estimate_mixprop}
\alias{estimate_mixprop}
\title{Estimate mixture proportions of a mixture g given noisy (error-prone) data from that mixture.}
\usage{
estimate_mixprop(
  data,
  g,
  prior,
  optmethod = c("mixSQP", "mixEM", "mixVBEM", "cxxMixSquarem", "mixIP", "w_mixEM"),
  control,
  weights = NULL
)
}
\arguments{
\item{data}{list to be passed to log_comp_dens_conv; details depend on model}

\item{g}{an object representing a mixture distribution (eg normalmix for mixture of normals;
unimix for mixture of uniforms). The component parameters of g (eg the means and variances) specify the
components whose mixture proportions are to be estimated. The mixture proportions of g are the parameters to be estimated;
the values passed in may be used to initialize the optimization (depending on the optmethod used)}

\item{prior}{numeric vector indicating parameters of "Dirichlet prior"
on mixture proportions}

\item{optmethod}{name of function to use to do optimization}

\item{control}{list of control parameters to be passed to optmethod,
typically affecting things like convergence tolerance}

\item{weights}{vector of weights (for use with w_mixEM; in beta)}
}
\value{
list, including the final loglikelihood, the null loglikelihood,
an n by k likelihood matrix with (j,k)th element equal to \eqn{f_k(x_j)},
the fit
and results of optmethod
}
\description{
Estimate mixture proportions of a mixture g given noisy (error-prone) data from that mixture.
}
\details{
This is used by the ash function. Most users won't need to call this directly, but is
exported for use by some other related packages.
}
