Discrete and Continous Hidden Markov implementation along with distribution estimation of observation per states. The states can be mapped according to ascending or descending order. For continous it is using Gaussian and for discrete multinomial distributions.
Auto HMM: Automatic Discrete and Continous HMM including Model selection
R codes for implementing Hidden Markov Model.
If you find this package useful or if you use it in your research or work please consider citing it as follows:
@article{tadayon2020comparative,
title={Comparative analysis of the hidden markov model and lstm: A simulative approach},
author={Tadayon, Manie and Pottie, Greg},
journal={arXiv preprint arXiv:2008.03825},
year={2020}
}
For more information, please refer to my Youtube videos:
https://www.youtube.com/watch?v=1b-sd7gulFk&ab_channel=AIandMLFundamentals
https://www.youtube.com/watch?v=ieU8JFLRw2k&ab_channel=AIandMLFundamentals
This code is released under the MIT liecense.