Large-Deviation Probabilities for One-Dimensional Markov Chains. Part 2: Prestationary Distributions in the Exponential Case
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...
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Veröffentlicht in: | Theory of probability and its applications 2000-01, Vol.45 (3), p.379-405 |
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Sprache: | eng |
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Zusammenfassung: | 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 {\bf 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]). |
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ISSN: | 0040-585X 1095-7219 |
DOI: | 10.1137/S0040585X97978358 |