The Annals of Mathematical Statistics

Statistical Inference about Markov Chains

T. W. Anderson and Leo A. Goodman

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Abstract

Maximum likelihood estimates and their asymptotic distribution are obtained for the transition probabilities in a Markov chain of arbitrary order when there are repeated observations of the chain. Likelihood ratio tests and $\chi^2$-tests of the form used in contingency tables are obtained for testing the following hypotheses: (a) that the transition probabilities of a first order chain are constant, (b) that in case the transition probabilities are constant, they are specified numbers, and (c) that the process is a $u$th order Markov chain against the alternative it is $r$th but not $u$th order. In case $u = 0$ and $r = 1$, case (c) results in tests of the null hypothesis that observations at successive time points are statistically independent against the alternate hypothesis that observations are from a first order Markov chain. Tests of several other hypotheses are also considered. The statistical analysis in the case of a single observation of a long chain is also discussed. There is some discussion of the relation between likelihood ratio criteria and $\chi^2$-tests of the form used in contingency tables.

Article information

Source
Ann. Math. Statist., Volume 28, Number 1 (1957), 89-110.

Dates
First available in Project Euclid: 27 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aoms/1177707039

Digital Object Identifier
doi:10.1214/aoms/1177707039

Mathematical Reviews number (MathSciNet)
MR84903

Zentralblatt MATH identifier
0087.14905

JSTOR
links.jstor.org

Citation

Anderson, T. W.; Goodman, Leo A. Statistical Inference about Markov Chains. Ann. Math. Statist. 28 (1957), no. 1, 89--110. doi:10.1214/aoms/1177707039. https://projecteuclid.org/euclid.aoms/1177707039


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