Package: meteorits 0.1.1.9000

Florian Lecocq

meteorits: Mixture-of-Experts Modeling for Complex Non-Normal Distributions

Provides a unified mixture-of-experts (ME) modeling and estimation framework with several original and flexible ME models to model, cluster and classify heterogeneous data in many complex situations where the data are distributed according to non-normal, possibly skewed distributions, and when they might be corrupted by atypical observations. Mixtures-of-Experts models for complex and non-normal distributions ('meteorits') are originally introduced and written in 'Matlab' by Faicel Chamroukhi. The references are mainly the following ones. The references are mainly the following ones. Chamroukhi F., Same A., Govaert, G. and Aknin P. (2009) <doi:10.1016/j.neunet.2009.06.040>. Chamroukhi F. (2010) <https://chamroukhi.com/FChamroukhi-PhD.pdf>. Chamroukhi F. (2015) <arxiv:1506.06707>. Chamroukhi F. (2015) <https://chamroukhi.com/FChamroukhi-HDR.pdf>. Chamroukhi F. (2016) <doi:10.1109/IJCNN.2016.7727580>. Chamroukhi F. (2016) <doi:10.1016/j.neunet.2016.03.002>. Chamroukhi F. (2017) <doi:10.1016/j.neucom.2017.05.044>.

Authors:Faicel Chamroukhi [aut], Florian Lecocq [aut, trl, cre], Marius Bartcus [aut, trl]

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meteorits.pdf |meteorits.html✨
meteorits/json (API)
NEWS

# Install 'meteorits' in R:
install.packages('meteorits', repos = c('https://fchamroukhi.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/fchamroukhi/meteorits/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

artificial-intelligenceclusteringem-algorithmmixture-of-expertsneural-networksnon-linear-regressionpredictionrobust-learningskew-normalskew-tskewed-datastatistical-inferencestatistical-learningt-distributionunsupervised-learning

8 exports 3 stars 1.10 score 4 dependencies 11 scripts 135 downloads

Last updated 5 years agofrom:11c42aa94a. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 12 2024
R-4.5-win-x86_64NOTESep 12 2024
R-4.5-linux-x86_64NOTESep 12 2024
R-4.4-win-x86_64NOTESep 12 2024
R-4.4-mac-x86_64NOTESep 12 2024
R-4.4-mac-aarch64NOTESep 12 2024
R-4.3-win-x86_64NOTESep 12 2024
R-4.3-mac-x86_64NOTESep 12 2024
R-4.3-mac-aarch64NOTESep 12 2024

Exports:emNMoEemSNMoEemStMoEemTMoEsampleUnivNMoEsampleUnivSNMoEsampleUnivStMoEsampleUnivTMoE

Dependencies:MASSpracmaRcppRcppArmadillo

A-quick-tour-of-NMoE

Rendered fromA-quick-tour-of-NMoE.Rmdusingknitr::rmarkdownon Sep 12 2024.

Last update: 2019-09-20
Started: 2019-07-16

A-quick-tour-of-SNMoE

Rendered fromA-quick-tour-of-SNMoE.Rmdusingknitr::rmarkdownon Sep 12 2024.

Last update: 2019-09-20
Started: 2019-07-11

A-quick-tour-of-StMoE

Rendered fromA-quick-tour-of-StMoE.Rmdusingknitr::rmarkdownon Sep 12 2024.

Last update: 2019-09-20
Started: 2019-07-11

A-quick-tour-of-tMoE

Rendered fromA-quick-tour-of-tMoE.Rmdusingknitr::rmarkdownon Sep 12 2024.

Last update: 2019-09-20
Started: 2019-07-11

Readme and manuals

Help Manual

Help pageTopics
MEteorits: Mixtures-of-ExperTs modEling for cOmplex and non-noRmal dIsTributionsmeteorits-package meteorits
emNMoE implements the EM algorithm to fit a Normal Mixture of Experts (NMoE).emNMoE
emSNMoE implements the ECM algorithm to fit a Skew-Normal Mixture of Experts (SNMoE).emSNMoE
emStMoE implements the ECM algorithm to fit a Skew-t Mixture of Experts (StMoE).emStMoE
emTMoE implements the ECM algorithm to fit a t Mixture of Experts (TMoE).emTMoE
A Reference Class which represents a fitted NMoE model.ModelNMoE ModelNMoE-class
A Reference Class which represents a fitted SNMoE model.ModelSNMoE ModelSNMoE-class
A Reference Class which represents a fitted StMoE model.ModelStMoE ModelStMoE-class
A Reference Class which represents a fitted TMoE model.ModelTMoE ModelTMoE-class
A Reference Class which contains parameters of a NMoE model.ParamNMoE ParamNMoE-class
A Reference Class which contains parameters of a SNMoE model.ParamSNMoE ParamSNMoE-class
A Reference Class which contains parameters of a StMoE model.ParamStMoE ParamStMoE-class
A Reference Class which contains parameters of a TMoE model.ParamTMoE ParamTMoE-class
Draw a sample from a normal mixture of linear experts model.sampleUnivNMoE
Draw a sample from a skew-normal mixture of linear experts model.sampleUnivSNMoE
Draw a sample from a univariate skew-t mixture.sampleUnivStMoE
Draw a sample from a univariate t mixture of experts (TMoE).sampleUnivTMoE
A Reference Class which contains statistics of a NMoE model.StatNMoE StatNMoE-class
A Reference Class which contains statistics of a SNMoE model.StatSNMoE StatSNMoE-class
A Reference Class which contains statistics of a StMoE model.StatStMoE StatStMoE-class
A Reference Class which contains statistics of a TMoE model.StatTMoE StatTMoE-class
Global Annual Temperature Anomalies (Land Meteorological Stations) (1880-2015)tempanomalies