To cite the toolbox samurais in a publication please use the following reference. To cite the corresponding paper for a specific package from samurais (e.g RHLP, HMMR, PWR, etc), please choose the reference(s) from the list provided below.

Chamroukhi F, Bartcus M, Lecocq F (2019). samurais: Statistical Models for the Unsupervised segmentatIon of Time-Series (SaMUraiS). R package version 0.1.0, https://github.com/fchamroukhi/SaMUraiS.

Chamroukhi F, Nguyen H (2019). “Model-Based Clustering and Classification of Functional Data.” Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. doi:10.1002/widm.1298, https://chamroukhi.com/papers/MBCC-FDA.pdf.

Chamroukhi F (2015). Statistical learning of latent data models for complex data analysis. Habilitation Thesis (HDR), Universit'e de Toulon.

Chamroukhi F, Trabelsi D, Mohammed S, Oukhellou L, Amirat Y (2013). “Joint segmentation of multivariate time series with hidden process regression for human activity recognition.” Neurocomputing, 120, 633–644. https://chamroukhi.com/papers/chamroukhi_et_al_neucomp2013b.pdf.

Trabelsi D, Mohammed S, Chamroukhi F, Oukhellou L, Amirat Y (2013). “An unsupervised approach for automatic activity recognition based on Hidden Markov Model Regression.” IEEE Transactions on Automation Science and Engineering, 3(10), 829–335. https://chamroukhi.com/papers/Chamroukhi-MHMMR-IeeeTase.pdf.

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

Chamroukhi F, Samé A, Govaert G, Aknin P (2010). “A hidden process regression model for functional data description. Application to curve discrimination.” Neurocomputing, 73(7-9), 1210–1221. https://chamroukhi.com/papers/chamroukhi_neucomp_2010.pdf.

Chamroukhi F, Samé A, Govaert G, Aknin P (2009). “Time series modeling by a regression approach based on a latent process.” Neural Networks, 22(5-6), 593–602. https://chamroukhi.com/papers/Chamroukhi_Neural_Networks_2009.pdf.

Corresponding BibTeX entries:

  @Manual{,
    title = {samurais: Statistical Models for the Unsupervised
      segmentatIon of Time-Series (SaMUraiS)},
    author = {F. Chamroukhi and M. Bartcus and F. Lecocq},
    year = {2019},
    note = {R package version 0.1.0},
    url = {https://github.com/fchamroukhi/SaMUraiS},
  }

  @Article{,
    title = {Model-Based Clustering and Classification of Functional
      Data},
    author = {F. Chamroukhi and Hien D. Nguyen},
    journal = {Wiley Interdisciplinary Reviews: Data Mining and
      Knowledge Discovery},
    year = {2019},
    url = {https://chamroukhi.com/papers/MBCC-FDA.pdf},
    doi = {10.1002/widm.1298},
  }

  @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)}},
  }

  @Article{,
    title = {Joint segmentation of multivariate time series with hidden
      process regression for human activity recognition},
    author = {F. Chamroukhi and D. Trabelsi and S. Mohammed and L.
      Oukhellou and Y. Amirat},
    journal = {Neurocomputing},
    year = {2013},
    volume = {120},
    publisher = {Elsevier},
    pages = {633--644},
    url =
      {https://chamroukhi.com/papers/chamroukhi_et_al_neucomp2013b.pdf},
  }

  @Article{,
    title = {An unsupervised approach for automatic activity
      recognition based on Hidden Markov Model Regression},
    author = {D. Trabelsi and S. Mohammed and F. Chamroukhi and L.
      Oukhellou and Y. Amirat},
    journal = {IEEE Transactions on Automation Science and
      Engineering},
    year = {2013},
    volume = {3},
    number = {10},
    pages = {829--335},
    url =
      {https://chamroukhi.com/papers/Chamroukhi-MHMMR-IeeeTase.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 = {A hidden process regression model for functional data
      description. Application to curve discrimination},
    author = {F. Chamroukhi and A. Sam\'{e} and G. Govaert and P.
      Aknin},
    journal = {Neurocomputing},
    year = {2010},
    volume = {73},
    number = {7-9},
    pages = {1210--1221},
    url = {https://chamroukhi.com/papers/chamroukhi_neucomp_2010.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},
    publisher = {Elsevier Science Ltd.},
    year = {2009},
    volume = {22},
    number = {5-6},
    pages = {593--602},
    url =
      {https://chamroukhi.com/papers/Chamroukhi_Neural_Networks_2009.pdf},
  }