LogLikelihood4Mixtures {AdaptGauss}

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)