tsBNgen: A Python Library to Generate Time Series Data Based on an Arbitrary Bayesian Network Structure
tsBNgen is a Python package to generate time series data based on an arbitrary Bayesian Network Structures.
If you find this package useful or if you use it in your research or work please consider citing it as follows:
@article{tadayon2020tsbngen,
title={tsBNgen: A Python Library to Generate Time Series Data from an Arbitrary Dynamic Bayesian Network Structure},
author={Tadayon, Manie and Pottie, Greg},
journal={arXiv preprint arXiv:2009.04595},
year={2020}
}
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It handles discrete nodes, continous nodes and hybrid (Mixture of discrete and continuous) network.
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It uses multinomila distribution for the discrete nodes and Gaussian distribution for the continuous nodes.
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It handles arbitrary Bayesian network structure.
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It supports arbitrary loopback values.
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The code can be modified easily to handle arbitrary static and temporal structures.
To run this code either clone this repo or use the package distribution in PyPI using the following commands:
pip install tsBNgenThen Run through the set of examples in
Time_Series_Generation_Examples.ipynb
For more information on how to use the package please visit the following:
- Watch my Youtube tutorial (I go over the package) Watch the videos
- Original paper
- Documentation in PDF available in this repository.
This software is released under the MIT liecense.