LogLikelihood4Mixtures

Computes the LogLikelihood for Gaussian Mixture Models.

Multimodal distributions can be modelled as a mixture of components. The model is derived using the Pareto Density Estimation (PDE) for an estimation of the pdf. PDE has been designed in particular to identify groups/classes in a dataset. Precise limits for the classes can be calculated using the theorem of Bayes. Verification of the model is possible by QQ plot, Chi-squared test and Kolmogorov-Smirnov test. The package is based on the publication of Ultsch, A., Thrun, M.C., Hansen-Goos, O., Lotsch, J. (2015) <DOI:10.3390/ijms161025897>.

Michael Thrun

AdaptGauss

Gaussian Mixture Models (GMM)

Onno Hansen-Goos

Rabea Griese

Catharina Lippmann

Florian Lerch

Quirin Stier

Jorn Lotsch

Luca Brinkmann

Alfred Ultsch

LogLikelihood4Mixtures function

<dl> <dt>Data</dt>
<dd>Data for empirical PDF. Has to be an Array of values. NaNs
 and NULLs will be deleted</dd> <dt>Means</dt>
<dd>Optional: Means of gaussians of GMM.</dd> <dt>SDs</dt>
<dd>Optional: StandardDevations of gaussians of GMM. (Has to be the same length as Means)</dd> <dt>Weights</dt>
<dd>Optional: Weights of gaussians of GMM. (Has to be the same length as Means)</dd> <dt>IsLogDistribution</dt>
<dd>Optional, ==1 if distribution(i) is a LogNormal, default vector of zeros of length 1:L</dd>	</dl>

Arguments

Author

LogLikelihood for Gaussian Mixture Models — LogLikelihood4Mixtures

<dl>

 <dt>Data</dt>
<dd>Data for empirical PDF. Has to be an Array of values. NaNs
 and NULLs will be deleted</dd>

 <dt>Means</dt>
<dd>Optional: Means of gaussians of GMM.</dd>

 <dt>SDs</dt>
<dd>Optional: StandardDevations of gaussians of GMM. (Has to be the same length as Means)</dd>

 <dt>Weights</dt>
<dd>Optional: Weights of gaussians of GMM. (Has to be the same length as Means)</dd>

 <dt>IsLogDistribution</dt>
<dd>Optional, ==1 if distribution(i) is a LogNormal, default vector of zeros of length 1:L</dd>

	</dl>

LogLikelihood for Gaussian Mixture Models

LogLikelihood4Mixtures: LogLikelihood for Gaussian Mixture Models

Description

Usage

Value

Arguments

Author

References