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.
- Python 3.6
- Numpy
- Scipy
- Pickle5
- Futures
- Scikit-learn
python3 -O run_toy_example.py