The Annals of Applied Statistics

Distributions associated with general runs and patterns in hidden Markov models

John A. D. Aston and Donald E. K. Martin

Full-text: Open access

Abstract

This paper gives a method for computing distributions associated with patterns in the state sequence of a hidden Markov model, conditional on observing all or part of the observation sequence. Probabilities are computed for very general classes of patterns (competing patterns and generalized later patterns), and thus, the theory includes as special cases results for a large class of problems that have wide application. The unobserved state sequence is assumed to be Markovian with a general order of dependence. An auxiliary Markov chain is associated with the state sequence and is used to simplify the computations. Two examples are given to illustrate the use of the methodology. Whereas the first application is more to illustrate the basic steps in applying the theory, the second is a more detailed application to DNA sequences, and shows that the methods can be adapted to include restrictions related to biological knowledge.

Article information

Source
Ann. Appl. Stat. Volume 1, Number 2 (2007), 585-611.

Dates
First available in Project Euclid: 30 November 2007

Permanent link to this document
http://projecteuclid.org/euclid.aoas/1196438032

Digital Object Identifier
doi:10.1214/07-AOAS125

Mathematical Reviews number (MathSciNet)
MR2415748

Zentralblatt MATH identifier
1126.62008

Keywords
Competing patterns CpG islands finite Markov chain imbedding generalized later patterns higher-order hidden Markov models sooner/later waiting time distributions

Citation

Aston, John A. D.; Martin, Donald E. K. Distributions associated with general runs and patterns in hidden Markov models. Ann. Appl. Stat. 1 (2007), no. 2, 585--611. doi:10.1214/07-AOAS125. http://projecteuclid.org/euclid.aoas/1196438032.


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