This package is intended to expand the 'stats' package so as
Imports: statmod, stats, shiny, dplyr, ggplot2, plotly, tippy,

Suggests: learnr, knitr, rmarkdown, spelling, testthat

Title: Fitting Multiple Parametric Distributions
Author: Benedikt Geier [aut], Borui Niklas Zhu [cre, aut], Moritz Kern [aut], Manuel J. Hentschel [aut], Kiril Dik [aut], Moritz Lauff [aut], Tim Glockner [aut], Adrian Heppeler [aut], Nadine Tampe [aut], Leonardo Vela [aut], Till Freihaut [aut], Niclas Lietzow [aut], Helene Peter [aut], Martin Schlather [aut, cre], Yiqi Li [ctb]
Maintainer: Borui Niklas Zhu <bzhu@mail.uni-mannheim.de>
Description: Given an univariate dataset, returns the best fitting parameter families, as defined in Shao (2003) <doi:10.1007/B97553>, including their parameter estimates via maximum likelihood.
Imports: utils, stats, stringr, datasets, graphics, grDevices, methods,

Author: Florian Lerch, Jorn Lotsch, Alfred Ultsch
Description: 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 maximisation as is used in Expectation maximisation. 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>.
Imports: ggplot2, GA, AdaptGauss, graphics, stats, utils
Packaged: 2019-03-14 09:36:52 UTC; florianlerch

Description: 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>.
Packaged: 2019-11-25 11:53:58 UTC; florianlerch