The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
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>.
Version: | 1.2.6 |
Imports: | ggplot2, GA, AdaptGauss, graphics, stats, utils, pracma |
Suggests: | parallelDist |
Published: | 2020-02-12 |
DOI: | 10.32614/CRAN.package.DistributionOptimization |
Author: | Florian Lerch, Jorn Lotsch, Alfred Ultsch |
Maintainer: | Florian Lerch <lerch at mathematik.uni-marburg.de> |
License: | MIT + file LICENSE |
NeedsCompilation: | no |
CRAN checks: | DistributionOptimization results |
Reference manual: | DistributionOptimization.pdf |
Package source: | DistributionOptimization_1.2.6.tar.gz |
Windows binaries: | r-devel: DistributionOptimization_1.2.6.zip, r-release: DistributionOptimization_1.2.6.zip, r-oldrel: DistributionOptimization_1.2.6.zip |
macOS binaries: | r-release (arm64): DistributionOptimization_1.2.6.tgz, r-oldrel (arm64): DistributionOptimization_1.2.6.tgz, r-release (x86_64): DistributionOptimization_1.2.6.tgz, r-oldrel (x86_64): DistributionOptimization_1.2.6.tgz |
Old sources: | DistributionOptimization archive |
Reverse imports: | opGMMassessment |
Please use the canonical form https://CRAN.R-project.org/package=DistributionOptimization to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.