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VIII.—The Central Limit Theorem for a Convergent Non-homogeneous Finite Markov Chain*

Published online by Cambridge University Press:  14 February 2012

J. L. Mott
Affiliation:
Department of Mathematics, University of Edinburgh.

Synopsis

The distribution of xn, the number of occurrences of a given one of k possible states of a non-homogeneous Markov chain {Pj} in n successive trials, is considered. It is shown that if PnP, a positive-regular stochastic matrix, as n → ∞ then the distribution about its mean of xn/n½ tends to normality, and that the variance tends to that of the corresponding distribution associated with the homogeneous chain {P}.

Type
Research Article
Copyright
Copyright © Royal Society of Edinburgh 1959

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References

References to Literature

Dobrǔsin, R. L., 1955. “Central Limit Theorem for Non-stationary Markov Chains”, C.R. Acad. Sci. U.R.S.S., 162, 58.Google Scholar
Dobrǔsin, R. L., 1956 a. “On the Condition of the Central Limit Theorem for Inhomogeous Markov Chains”, C.R. Acad. Sci. U.R.S.S., 108, 10041006.Google Scholar
Dobrǔsin, R. L., 1956 b. “Central Limit Theorem for Non-stationary Markov Chains”, Teor. Veroyatnostei, 1, 7289 and 365-425.Google Scholar
Fréchet, M., 1938. Recherches théoriques modernes sur la théorie des probabilités, Second Livre. Paris.Google Scholar
Fréchet, M., and Shohat, J., 1931. “A Proof of the Generalized Second Limit-theorem in the Theory of Probability”, Trans. Amer. Math. Soc., 33, 533543.CrossRefGoogle Scholar
Mott, J. L., 1957. “Conditions for the Ergodicity of Non-homogeneous Finite Markov Chains”, Proc. Roy. Soc. Edin. A, 64, 369380.Google Scholar