To cite the package meteorits in a publication please use the following reference. To cite the corresponding paper for a specific package from meteorits (e.g NMoE, SNMoE, tMoE, StMoE, etc), please choose the reference(s) from the list provided below.

Chamroukhi F, Lecocq F, Bartcus M (2019). meteorits: Mixtures-of-Experts Modeling for Complex and Non-Normal Distributions ('MEteorits'). R package version 0.1.1, https://github.com/fchamroukhi/MEteorits.

Huynh B, Chamroukhi F (2019). “Estimation and Feature Selection in Mixtures of Generalized Linear Experts Models.” Journal de la Société Française de Statistique. https://chamroukhi.com/papers/Chamroukhi_Huynh_jsfds-published.pdf.

Chamroukhi F, Huynh B (2019). “Regularized Maximum Likelihood Estimation and Feature Selection in Mixtures-of-Experts Models.” Journal de la Société Française de Statistique, 160(1), 57–85.

Nguyen H, Chamroukhi F (2018). “Practical and theoretical aspects of mixture-of-experts modeling: An overview.” Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, e1246–n/a. doi: 10.1002/widm.1246, https://chamroukhi.com/papers/Nguyen-Chamroukhi-MoE-DMKD-2018.

Chamroukhi F (2017). “Skew t mixture of experts.” Neurocomputing - Elsevier, 266, 390–408. https://chamroukhi.com/papers/STMoE.pdf.

Chamroukhi F (2016). “Robust mixture of experts modeling using the t-distribution.” Neural Networks - Elsevier, 79, 20–36. https://chamroukhi.com/papers/TMoE.pdf.

Chamroukhi F (2016). “Skew-Normal Mixture of Experts.” In The International Joint Conference on Neural Networks (IJCNN). https://chamroukhi.com/papers/Chamroukhi-SNMoE-IJCNN2016.pdf.

Chamroukhi F (2015). Statistical learning of latent data models for complex data analysis. Habilitation Thesis (HDR), Université de Toulon. https://chamroukhi.com/Dossier/FChamroukhi-Habilitation.pdf.

Chamroukhi F (2010). Hidden process regression for curve modeling, classification and tracking. Ph.D. Thesis, Université de Technologie de Compiègne. https://chamroukhi.com/papers/FChamroukhi-Thesis.pdf.

Chamroukhi F, Samé A, Govaert G, Aknin P (2009). “Time series modeling by a regression approach based on a latent process.” Neural Networks Elsevier Science Ltd., 22(5-6), 593–602.

Corresponding BibTeX entries:

  @Manual{,
    title = {meteorits: Mixtures-of-Experts Modeling for Complex and
      Non-Normal Distributions ('MEteorits')},
    author = {F. Chamroukhi and F. Lecocq and M. Bartcus},
    year = {2019},
    note = {R package version 0.1.1},
    url = {https://github.com/fchamroukhi/MEteorits},
  }

  @Article{,
    author = {B-T. Huynh and F. Chamroukhi},
    journal = {Journal de la Soci\'{e}t\'{e} Fran\c{c}aise de
      Statistique},
    title = {Estimation and Feature Selection in Mixtures of
      Generalized Linear Experts Models},
    year = {2019},
    url =
      {https://chamroukhi.com/papers/Chamroukhi_Huynh_jsfds-published.pdf},
  }

  @Article{,
    title = {Regularized Maximum Likelihood Estimation and Feature
      Selection in Mixtures-of-Experts Models},
    author = {F. Chamroukhi and Bao T. Huynh},
    journal = {Journal de la Soci\'{e}t\'{e} Fran\c{c}aise de
      Statistique},
    volume = {160},
    number = {1},
    pages = {57--85},
    year = {2019},
  }

  @Article{,
    title = {Practical and theoretical aspects of mixture-of-experts
      modeling: An overview},
    author = {Hien D. Nguyen and F. Chamroukhi},
    journal = {Wiley Interdisciplinary Reviews: Data Mining and
      Knowledge Discovery},
    publisher = {Wiley Periodicals, Inc},
    year = {2018},
    pages = {e1246--n/a},
    doi = {10.1002/widm.1246},
    url =
      {https://chamroukhi.com/papers/Nguyen-Chamroukhi-MoE-DMKD-2018},
  }

  @Article{,
    title = {Skew t mixture of experts},
    author = {F. Chamroukhi},
    journal = {Neurocomputing - Elsevier},
    year = {2017},
    volume = {266},
    pages = {390--408},
    url = {https://chamroukhi.com/papers/STMoE.pdf},
  }

  @Article{,
    title = {Robust mixture of experts modeling using the
      t-distribution},
    author = {F. Chamroukhi},
    journal = {Neural Networks - Elsevier},
    year = {2016},
    volume = {79},
    pages = {20--36},
    url = {https://chamroukhi.com/papers/TMoE.pdf},
  }

  @InProceedings{,
    title = {Skew-Normal Mixture of Experts},
    author = {F. Chamroukhi},
    booktitle = {The International Joint Conference on Neural Networks
      (IJCNN)},
    year = {2016},
    url =
      {https://chamroukhi.com/papers/Chamroukhi-SNMoE-IJCNN2016.pdf},
  }

  @PhdThesis{,
    title = {Statistical learning of latent data models for complex
      data analysis},
    author = {F. Chamroukhi},
    school = {Universit\'{e} de Toulon},
    year = {2015},
    type = {Habilitation Thesis (HDR)},
    url =
      {https://chamroukhi.com/Dossier/FChamroukhi-Habilitation.pdf},
  }

  @PhdThesis{,
    title = {Hidden process regression for curve modeling,
      classification and tracking},
    author = {F. Chamroukhi},
    school = {Universit\'{e} de Technologie de Compi\`{e}gne},
    year = {2010},
    type = {Ph.D. Thesis},
    url = {https://chamroukhi.com/papers/FChamroukhi-Thesis.pdf},
  }

  @Article{,
    title = {Time series modeling by a regression approach based on a
      latent process},
    author = {F. Chamroukhi and A. Sam\'{e} and G. Govaert and P.
      Aknin},
    journal = {Neural Networks Elsevier Science Ltd.},
    year = {2009},
    volume = {22},
    number = {5-6},
    pages = {593--602},
  }