CDFMixtures

returns the cdf (cumulative distribution function) of a mixture model of gaussian or log gaussians

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

CDFMixtures function

<dl> <dt>Kernels</dt>
<dd>at these locations N(Means,Sdevs)*Weights is used for cdf calcuation, NOTE: Kernels are usually (but not necessarily) sorted and unique</dd> <dt>Means</dt>
<dd>vector(1:L), Means of Gaussians, L == Number of Gaussians</dd> <dt>SDs</dt>
<dd>estimated Gaussian Kernels = standard deviations</dd> <dt>Weights</dt>
<dd>optional, relative number of points in Gaussians (prior probabilities): 
 sum(Weights) ==1, default weight is 1/L</dd> <dt>IsLogDistribution</dt>
<dd>Optional, if IsLogDistribution(i)==1, then mixture is lognormal
 default == 0*(1:L)</dd></dl>

Arguments

Author

cumulative distribution of mixture model — CDFMixtures

<dl>

 <dt>Kernels</dt>
<dd>at these locations N(Means,Sdevs)*Weights is used for cdf calcuation, NOTE: Kernels are usually (but not necessarily) sorted and unique</dd>

 <dt>Means</dt>
<dd>vector(1:L), Means of Gaussians, L == Number of Gaussians</dd>

 <dt>SDs</dt>
<dd>estimated Gaussian Kernels = standard deviations</dd>

 <dt>Weights</dt>
<dd>optional, relative number of points in Gaussians (prior probabilities): 
 sum(Weights) ==1, default weight is 1/L</dd>

 <dt>IsLogDistribution</dt>
<dd>Optional, if IsLogDistribution(i)==1, then mixture is lognormal
 default == 0*(1:L)</dd>

</dl>

cumulative distribution of mixture model

CDFMixtures: cumulative distribution of mixture model

Description

Usage

Value

Arguments

Author

See Also