hmmTensor
Hidden Markov Model by Matrix and Tensor Decomposition
Solves Hidden Markov Models (HMMs) via matrix and tensor decomposition. Converts observation sequences to co-occurrence matrices/tensors and applies Symmetric Non-negative Matrix Factorization (symNMF), Singular Value Decomposition (SVD), CANDECOMP/PARAFAC (CP) decomposition, or Tensor-Train (TT) decomposition to recover HMM parameters. Also provides standard HMM algorithms (Forward, Backward, Viterbi, Baum-Welch) for comparison. The spectral learning approach for HMMs is based on Hsu, Kakade, and Zhang (2012) <doi:10.1016/j.jcss.2011.12.025>. The symNMF method is described in Kuang, Yun, and Park (2015) <doi:10.1007/s10898-014-0247-2>. The Tensor-Train decomposition is described in Oseledets (2011) <doi:10.1137/090752286>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | hmmTensor_0.1.0.tar.gz |
49.3 KiB |
0.1.0 |
rolling linux/noble R-4.5 | hmmTensor_0.1.0.tar.gz |
49.2 KiB |
0.1.0 |
rolling source/ R- | hmmTensor_0.1.0.tar.gz |
10.0 KiB |
0.1.0 |
latest linux/jammy R-4.5 | hmmTensor_0.1.0.tar.gz |
49.3 KiB |
0.1.0 |
latest linux/noble R-4.5 | hmmTensor_0.1.0.tar.gz |
49.2 KiB |
0.1.0 |
latest source/ R- | hmmTensor_0.1.0.tar.gz |
10.0 KiB |
0.1.0 |
2026-04-23 source/ R- | hmmTensor_0.1.0.tar.gz |
0 B |