meteorits0.1.1 package

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

emNMoE

emNMoE implements the EM algorithm to fit a Normal Mixture of Experts ...

emSNMoE

emSNMoE implements the ECM algorithm to fit a Skew-Normal Mixture of E...

emStMoE

emStMoE implements the ECM algorithm to fit a Skew-t Mixture of Expert...

emTMoE

emTMoE implements the ECM algorithm to fit a t Mixture of Experts (TMo...

meteorits-package

MEteorits: Mixtures-of-ExperTs modEling for cOmplex and non-noRmal dIs...

ModelNMoE-class

A Reference Class which represents a fitted NMoE model.

ModelSNMoE-class

A Reference Class which represents a fitted SNMoE model.

ModelStMoE-class

A Reference Class which represents a fitted StMoE model.

ModelTMoE-class

A Reference Class which represents a fitted TMoE model.

ParamNMoE-class

A Reference Class which contains parameters of a NMoE model.

ParamSNMoE-class

A Reference Class which contains parameters of a SNMoE model.

ParamStMoE-class

A Reference Class which contains parameters of a StMoE model.

ParamTMoE-class

A Reference Class which contains parameters of a TMoE model.

sampleUnivNMoE

Draw a sample from a normal mixture of linear experts model.

sampleUnivSNMoE

Draw a sample from a skew-normal mixture of linear experts model.

sampleUnivSTMoE

Draw a sample from a univariate skew-t mixture.

sampleUnivTMoE

Draw a sample from a univariate t mixture of experts (TMoE).

StatNMoE-class

A Reference Class which contains statistics of a NMoE model.

StatSNMoE-class

A Reference Class which contains statistics of a SNMoE model.

StatStMoE-class

A Reference Class which contains statistics of a StMoE model.

StatTMoE-class

A Reference Class which contains statistics of a TMoE model.

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>.

  • Maintainer: Florian Lecocq
  • License: GPL (>= 3)
  • Last published: 2020-01-10