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Teor. Veroyatnost. i Primenen., 2000 Volume 45, Issue 3, Pages 437–468 (Mi tvp479)

This article is cited in 11 papers

Large-deviation probabilities for one-dimensional Markov chains. Part 2: Prestationary distributions in the exponential case

A. A. Borovkov, D. A. Korshunov

Sobolev Institute of Mathematics, Siberian Branch of the Russian Academy of Sciences

Abstract: This paper continues investigations of [A. A. Borovkov and A. D. Korshunov, Theory Probab. Appl., 41 (1996), pp. 1–24]. We consider a time-homogeneous and asymptotically space-homogeneous Markov chain $\{X(n)\}$ that takes values on the real line and has increments possessing a finite exponential moment. The asymptotic behavior of the probability $\mathbf{P}\{X(n)\ge x\}$ is studied as $x\to\infty$ for fixed or growing values of time $n$. In particular, we extract the ranges of $n$ within which this probability is asymptotically equivalent to the tail of a stationary distribution $\pi(x)$ (the latter is studied in [A. A. Borovkov and A. D. Korshunov, Theory Probab. Appl., 41 (1996), pp. 1–24] and is detailed in section 27 of [A. A. Borovkov, Ergodicity and Stability of Stochastic Processes, Wiley, New York, 1998]).

Keywords: Markov chain, rough and exact asymptotic behavior of large-deviation probabilities, transition phenomena, invariant measure.

Received: 12.02.1999

DOI: 10.4213/tvp479


 English version:
Theory of Probability and its Applications, 2001, 45:3, 379–405

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