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.

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

A BibTeX entry for LaTeX users is

  @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},
  }

  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 (URL:
  https://doi.org/10.1002/widm.1298),
  <URL:https://chamroukhi.com/papers/MBCC-FDA.pdf>.

A BibTeX entry for LaTeX users is

  @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},
  }

  Chamroukhi F (2015). “Statistical learning of latent data models for
  complex data analysis”. Habilitation Thesis (HDR), Université de
  Toulon.

A BibTeX entry for LaTeX users is

  @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)}},
  }

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

A BibTeX entry for LaTeX users is

  @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},
  }

  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. <URL:
  https://chamroukhi.com/papers/Chamroukhi-MHMMR-IeeeTase.pdf>.

A BibTeX entry for LaTeX users is

  @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},
  }

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

A BibTeX entry for LaTeX users is

  @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},
  }

  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.  <URL:
  https://chamroukhi.com/papers/chamroukhi_neucomp_2010.pdf>.

A BibTeX entry for LaTeX users is

  @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},
  }

  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.
  <URL:https://chamroukhi.com/papers/Chamroukhi_Neural_Networks_2009.pdf>.

A BibTeX entry for LaTeX users is

  @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},
  }