CHERNOFF BOUNDS FOR DISCRIMINATING BETWEEN TWO MARKOV PROCESSES.

C. M. Newman; B. W. Stuck

doi:10.1080/17442507908833121

CHERNOFF BOUNDS FOR DISCRIMINATING BETWEEN TWO MARKOV PROCESSES.

C. M. Newman, B. W. Stuck

Mathematics

Research output: Contribution to journal › Article › peer-review

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 language	English (US)
Pages (from-to)	139-153
Number of pages	15
Journal	Stochastics
Volume	2
Issue number	3
DOIs	https://doi.org/10.1080/17442507908833121
State	Published - 1979

ASJC Scopus subject areas

Statistics and Probability
Modeling and Simulation

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10.1080/17442507908833121

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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.",

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AB - 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.

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CHERNOFF BOUNDS FOR DISCRIMINATING BETWEEN TWO MARKOV PROCESSES.

Abstract

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