Package: hmmTensor
Type: Package
Title: Hidden Markov Model by Matrix and Tensor Decomposition
Version: 0.1.0
Authors@R: person(given = "Koki",
    family = "Tsuyuzaki",
    role = c("aut", "cre"),
    email = "k.t.the-answer@hotmail.co.jp")
Description: 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>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: rTensor, symTensor, methods, stats
Suggests: testthat
RoxygenNote: 7.3.2
NeedsCompilation: no
Packaged: 2026-05-19 11:03:11 UTC; koki
Author: Koki Tsuyuzaki [aut, cre]
Maintainer: Koki Tsuyuzaki <k.t.the-answer@hotmail.co.jp>
Repository: CRAN
Date/Publication: 2026-05-27 09:10:02 UTC
