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PHMC-MLAR

Partially Hidden Markov Chain Multivariate Linear AutoRegressive (PHMC-MLAR)

This package contains the software programs designed for the PHMC-MLAR model. It includes a learning algorithm, a prediction function and a state inference algorithm.

If you use this model in your work, please refer to it as follows:

F. Dama and C. Sinoquet (2023). Partially Hidden Markov Chain Multivariate Linear Autoregressive model: inference and forecasting - application to machine health prognostics. Machine Learning, 112(1), 45-97.

This package has been implemented by Fatoumata Dama, PhD student (2019-2022), Nantes University, France.

Fatoumata Dama was supported by a PhD scholarship granted by the French Ministery for Higher Education, Research and Innovation. She worked under the supervision of Christine Sinoquet, Associate Professor, PhD supervisor, LS2N / UMR CNRS 6004 (Digital Science Institute of Nantes), Nantes University, France.

Requirements

  • Python 3.6
  • Numpy
  • Scipy
  • Pickle5
  • Futures
  • Scikit-learn

Launch the toy example

 python3 -O run_toy_example.py