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

*ashr*version 2.2-63 Index]