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A Sufficient Condition for Reducing Recursions in Hidden Markov Models

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Abstract

In hidden Markov models, the probability of observing a set of strings can be computed using recursion relations. We construct a sufficient condition for simplifying the recursion relations for a certain class of hidden Markov models. If the condition is satisfied, then one can construct a reduced recursion where the dependence on Markov states completely disappears. We discuss a specific example—namely, statistical multiple alignment based on the TKF-model—in which the sufficient condition is satisfied.

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Author notes

  1. Yun S. Song

    Present address: Department of Computer Science, University of California at Davis, Davis, CA, 95616, USA

Authors and Affiliations

  1. Department of Statistics, University of Oxford, 1 South Parks Road, Oxford, OX1 3TG, UK

    Yun S. Song

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  1. Yun S. Song
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Correspondence to Yun S. Song.

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Song, Y.S. A Sufficient Condition for Reducing Recursions in Hidden Markov Models. Bull. Math. Biol. 68, 361–384 (2006). https://doi.org/10.1007/s11538-005-9045-9

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  • DOI: https://doi.org/10.1007/s11538-005-9045-9

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