LogLikelihood4Mixtures {AdaptGauss} | R Documentation |

## LogLikelihood for Gaussian Mixture Models

### Description

Computes the LogLikelihood for Gaussian Mixture Models.

### Usage

```
LogLikelihood4Mixtures(Data, Means, SDs, Weights, IsLogDistribution)
```

### Arguments

`Data` |
Data for empirical PDF. Has to be an Array of values. NaNs and NULLs will be deleted |

`Means` |
Optional: Means of gaussians of GMM. |

`SDs` |
Optional: StandardDevations of gaussians of GMM. (Has to be the same length as Means) |

`Weights` |
Optional: Weights of gaussians of GMM. (Has to be the same length as Means) |

`IsLogDistribution` |
Optional, ==1 if distribution(i) is a LogNormal, default vector of zeros of length 1:L |

### Value

List with

`LogLikelihood` |
LogLikelihood = = sum(log(PDFmixture) |

`LogPDF` |
=log(PDFmixture) |

`PDFmixture` |
die Probability density function for each point |

### Author(s)

Alfred Ultsch, Catharina Lippmann

### References

Pattern Recogintion and Machine Learning, C.M. Bishop, 2006, isbn: ISBN-13: 978-0387-31073-2, p. 433 (9.14)

[Package

*AdaptGauss*version 1.6 Index]