Symlognpdf

Symlognpdf is an internal function for AdaptLGL.

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

Symlognpdf function

<dl> <dt>Data</dt>
<dd>vector of data points used for sampling</dd> <dt>Mean</dt>
<dd>Mean of log Gaussian</dd> <dt>SD</dt>
<dd>Standard deviation of log Gaussian</dd></dl>

Arguments

computes a special case of log normal distribution density — Symlognpdf

<dl>

 <dt>Data</dt>
<dd>vector of data points used for sampling</dd>

 <dt>Mean</dt>
<dd>Mean of log Gaussian</dd>

 <dt>SD</dt>
<dd>Standard deviation of log Gaussian</dd>

</dl>

computes a special case of log normal distribution density

Symlognpdf: computes a special case of log normal distribution density

Description

Usage

Value

Arguments

See Also