CHERNOFF BOUNDS FOR DISCRIMINATING BETWEEN TWO MARKOV PROCESSES.

C. M. Newman, B. W. Stuck

Research output: Contribution to journalArticle

Abstract

A statistical hypothesis testing problem is considered where a sample function of a Markov process with one of two sets of known parameters is observed over a finite time interval. When a log likelihood ratio test is used to discriminate between the two sets of parameters, bounds are given on the probability of choosing an incorrect hypothesis, and on the total probability of error, for both discrete and continuous time parameter, and discrete and continuous state space. The asymptotic behavior of the bounds is examined as the observation interval becomes infinite.

Original languageEnglish (US)
Pages (from-to)139-153
Number of pages15
JournalStochastics
Volume2
Issue number3
DOIs
StatePublished - 1979

ASJC Scopus subject areas

  • Statistics and Probability
  • Modeling and Simulation

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