Duality Between the Local Score of One Sequence and Constrained Hidden Markov Model

We are interested here in a theoretical and practical approach for detecting atypical segments in a multi-state sequence. We prove in this article that the segmentation approach through an underlying constrained Hidden Markov Model (HMM) is equivalent to using the maximum scoring subsequence (also c...

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Veröffentlicht in:	Methodology and computing in applied probability Jg. 24; H. 3; S. 1411 - 1438
Hauptverfasser:	Mercier, Sabine, Nuel, Grégory
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.09.2022 Springer Nature B.V Springer Verlag
Schriftenreihe:	Methodology and Computing in Applied Probability
Schlagworte:	Adaptation Algorithms Business and Management Economics Electrical Engineering Equivalence Life Sciences Markov chains Mathematics Mathematics and Statistics Probability Segmentation Segments Statistics Maximum scoring subsequence 60J20 62M05 62C10 Local score HMM Forward/backward 60 Posterior distribution Biological sequence analysis 62F15 forward/backward maximum scoring subsequence posterior distribution biological sequence analysis
ISSN:	1387-5841, 1573-7713
Online-Zugang:	Volltext
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