Asymptotic risks of Viterbi segmentation

Abstract

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

Keywords

Hidden Markov model; Viterbi alignment; segmentation

Published in

Research report (Centre of Biostochastics)
2010, number: 2010:2, pages: 1-25
Publisher: Centre of Biostochastics

SLU Authors

• Kuljus, Kristi

  • Department of Forest Economics, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Probability Theory and Statistics


Permanent link to this page (URI)

https://res.slu.se/id/publ/29335