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Statistical Inference in Hidden Markov Models Using k-Segment Constraints
Hidden Markov models (HMMs) are one of the most widely used statistical methods for analyzing sequence data. However, the reporting of output from HMMs has largely been restricted to the presentation of the most-probable (MAP) hidden state sequence, found via the Viterbi algorithm, or the sequence o...
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| Udgivet i: | J Am Stat Assoc |
|---|---|
| Main Authors: | , , |
| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
Taylor & Francis
2016
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| Fag: | |
| Online adgang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4867884/ https://ncbi.nlm.nih.gov/pubmed/27226674 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/01621459.2014.998762 |
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