Package: mclustAddons 0.9.1
Luca Scrucca
mclustAddons: Addons for the 'mclust' Package
Extend the functionality of the 'mclust' package for Gaussian finite mixture modeling by including: density estimation for data with bounded support (Scrucca, 2019 <doi:10.1002/bimj.201800174>); modal clustering using MEM (Modal EM) algorithm for Gaussian mixtures (Scrucca, 2021 <doi:10.1002/sam.11527>); entropy estimation via Gaussian mixture modeling (Robin & Scrucca, 2023 <doi:10.1016/j.csda.2022.107582>); Gaussian mixtures modeling of financial log-returns (Scrucca, 2024 <doi:10.3390/e26110907>).
Authors:
mclustAddons_0.9.1.tar.gz
mclustAddons_0.9.1.tar.gz(r-4.5-noble)mclustAddons_0.9.1.tar.gz(r-4.4-noble)
mclustAddons_0.9.1.tgz(r-4.4-emscripten)mclustAddons_0.9.1.tgz(r-4.3-emscripten)
mclustAddons.pdf |mclustAddons.html✨
mclustAddons/json (API)
NEWS
# Install 'mclustAddons' in R: |
install.packages('mclustAddons', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/mclust-org/mclustaddons/issues
Pkgdown:https://mclust-org.github.io
Last updated 28 days agofrom:9adbbeddcd. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 27 2024 |
R-4.5-linux-x86_64 | OK | Nov 27 2024 |
Exports:as.densityMclustBoundedas.MclustBoundedbits2natscdfDensityBoundeddensityMclustBoundeddensityMclustBounded.diagnosticEntropyGaussEntropyGMMESGaussianMixtureMEMgmm2margParamsGMMlogreturnMclustBoundedMclustBoundedParametersmclustMarginalParamsMclustMEMnats2bitsquantileDensityBoundedrangepowerBackTransformrangepowerTransformVaR
Dependencies:base64encbslibcachemclicodetoolsdigestdoParalleldoRNGevaluatefastmapfontawesomeforeachfsgluehighrhtmltoolsiteratorsjquerylibjsonliteknitrlifecyclemclustmemoisemimeR6rappdirsRcppRcppArmadillorlangrmarkdownrngtoolssasstinytexxfunyaml
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Cumulative distribution and quantiles of univariate model-based mixture density estimation for bounded data | cdfDensityBounded densityMclustBounded.diagnostic quantileDensityBounded |
Model-based mixture density estimation for bounded data | densityMclustBounded print.densityMclustBounded print.summary.densityMclustBounded summary.densityMclustBounded |
Gaussian mixture-based estimation of entropy | bits2nats EntropyGauss EntropyGMM EntropyGMM.data.frame EntropyGMM.densityMclust EntropyGMM.densityMclustBounded EntropyGMM.matrix EntropyGMM.Mclust nats2bits |
Modal EM algorithm for Gaussian Mixtures | GaussianMixtureMEM |
Modeling log-returns distribution via Gaussian Mixture Models | GMMlogreturn summary.GMMlogreturn |
Gold price log-returns | gold |
Internal 'mclustAddons' functions | as.densityMclustBounded as.densityMclustBounded.default as.densityMclustBounded.MclustBounded as.MclustBounded as.MclustBounded.default as.MclustBounded.densityMclustBounded mclustAddons-internal |
Model-based clustering for bounded data | MclustBounded print.MclustBounded print.summary.MclustBounded summary.MclustBounded |
Recover parameters in the original scale | MclustBoundedParameters |
Marginal parameters from fitted GMMs via mclust | gmm2margParams mclustMarginalParams |
Modal EM algorithm for Gaussian Mixtures fitted via _mclust_ package | MclustMEM print.MclustMEM print.summary.MclustMEM summary.MclustMEM |
Plotting method for model-based mixture density estimation for bounded data | plot.densityMclustBounded |
Plotting method for model-based clustering of bounded data | plot.MclustBounded |
Plotting method for modal-clustering based on Gaussian Mixtures | plot.MclustMEM |
Model-based mixture density estimation for bounded data | predict.densityMclustBounded |
Model-based clustering estimation for bounded data | predict.MclustBounded |
Racial data | racial |
Range–power transformation | rangepowerBackTransform rangepowerTransform |
Suicide data | suicide |
Financial risk measures | ES VaR |
Risk measures from Gaussian mixtures modeling | ES.GMMlogreturn VaR.GMMlogreturn |