Asymptotic risks of Viterbi segmentation

Details Asymptotic risks of Viterbi segmentation Asymptotic risks of Viterbi segmentation

2010-02-18

arxiv.org/abs/1002.3509v2

Mathematics

Probability

23 pages

Scientific paper

We consider the maximum likelihood (Viterbi) alignment of a hidden Markov model (HMM). In an HMM, the underlying Markov chain is usually hidden and the Viterbi alignment is often used as the estimate of it. This approach will be referred to as the Viterbi segmentation. The goodness of the Viterbi segmentation can be measured by several risks. In this paper, we prove the existence of asymptotic risks. Being independent of data, the asymptotic risks can be considered as the characteristics of the model that illustrate the long-run behavior of the Viterbi segmentation.

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