R: Estimate mixture proportions of a mixture g given noisy...

estimate_mixprop {ashr} | R Documentation

## Estimate mixture proportions of a mixture g given noisy (error-prone) data from that mixture.

### Description

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

`data` | list to be passed to log_comp_dens_conv; details depend on model
`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)
`prior` | numeric vector indicating parameters of "Dirichlet prior" on mixture proportions
`optmethod` | name of function to use to do optimization
`control` | list of control parameters to be passed to optmethod, typically affecting things like convergence tolerance
`weights` | vector of weights (for use with w_mixEM; in beta)

### 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.

### Value

list, including the final loglikelihood, the null loglikelihood, an n by k likelihood matrix with (j,k)th element equal to f_k(x_j), the fit and results of optmethod

[Package ashr version 2.2-54 Index]