mixVBEM {ashr} | R Documentation |

## Estimate posterior distribution on mixture proportions of a mixture model by a Variational Bayes EM algorithm

### Description

Given the individual component likelihoods for a mixture model, estimates the posterior on the mixture proportions by an VBEM algorithm. Used by the ash main function; there is no need for a user to call this function separately, but it is exported for convenience.

### Usage

```
mixVBEM(matrix_lik, prior, pi_init = NULL, control = list())
```

### Arguments

`matrix_lik` |
a n by k matrix with (j,k)th element equal to |

`prior` |
a k vector of the parameters of the Dirichlet prior on |

`pi_init` |
the initial value of the posterior parameters. If not specified defaults to the prior parameters. |

`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). |

### Details

Fits a k component mixture model

`f(x|\pi) = \sum_k \pi_k f_k(x)`

to independent
and identically distributed data `x_1,\dots,x_n`

.
Estimates posterior on mixture proportions `\pi`

by Variational Bayes,
with a Dirichlet prior on `\pi`

.
Algorithm adapted from Bishop (2009), Pattern Recognition and Machine Learning, Chapter 10.

### Value

A list, whose components include point estimates (pihat),
the parameters of the fitted posterior on `\pi`

(pipost),
the bound on the log likelihood for each iteration (B)
and a flag to indicate convergence (converged).

*ashr*version 2.2-63 Index]