Fits Gaussian Mixtures by applying evolution. As fitness function a mixture of the chi square test for distributions and a novel measure for approximating the common area under curves between multiple Gaussians is used. The package presents an alternative to the commonly used Likelihood Maximization as is used in Expectation Maximization. The evolution is based on the 'GA' package: Luca Scrucca (2013) <doi:10.18637/jss.v053.i04> while the Gaussian Mixture Logic stems from 'AdaptGauss': Alfred Ultsch, Michael Thrun, Onno Hansen-Goos, Jorn Lotsch (2015) <doi:10.3390/ijms161025897>.

Fits Gaussian Mixtures by applying evolution. As fitness function a mixture of the chi square test for distributions and a novel measure for approximating the common area under curves between multiple Gaussians is used. The package presents an alternative to the commonly used Likelihood Maximization as is used in Expectation Maximization. The algorithm and applications of this package are published under: Lerch, F., Ultsch, A., Lotsch, J. (2020) <doi:10.1038/s41598-020-57432-w>. The evolution is based on the 'GA' package: Scrucca, L. (2013) <doi:10.18637/jss.v053.i04> while the Gaussian Mixture Logic stems from 'AdaptGauss': Ultsch, A, et al. (2015) <doi:10.3390/ijms161025897>.
ggplot2, GA, AdaptGauss, graphics, stats, utils, pracma

Powerful Goodness-of-Fit Tests Based on the Likelihood Ratio
Provides new types of omnibus tests which are generally much more powerful than traditional tests (including the Kolmogorov-Smirnov, Cramer-von Mises and Anderson-Darling tests),see Zhang (2002) <doi:10.1111/1467-9868.00337>.

This package contains utilities which are of use in the
packages I have developed for dealing with distributions.
Currently these packages are GeneralizedHyperbolic,
VarianceGamma, and SkewHyperbolic. Additional packages are
under development. Each of these packages requires
DistributionUtils. Functionality includes sample skewness and
kurtosis, log-histogram, moments by integration, changing the
pint about which a moment is calculated, functions for testing
distributions using inversion tests and the Massart inequality.