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August, 1982 A Limit Theorem for Slowly Increasing Occupation Times
Yuji Kasahara
Ann. Probab. 10(3): 728-736 (August, 1982). DOI: 10.1214/aop/1176993780

Abstract

Let $B_t$ be a two-dimensional Brownian motion and $f(x)$ be a bounded measurable function vanishing outside a compact set. Then $(1/\lambda) \int^{e^{\lambda t}}_0 f(B_s) ds$ converges to const. $\ell(M^{-1}(t), 0)$ as $\lambda \rightarrow \infty$, where $\ell(t, x)$ and $M(t)$ are the local time and the maximum process of a one-dimensional Brownian motion, respectively. In the present article we generalize this theorem for more general Markov processes as follows: Let $X_t$ be a Markov process and $f(x)$ be a nonnegative, bounded measurable function on the state space. If the expectation of $\int^t_0 f(X_s) ds$ is asymptotically equal to a slowly varying function $L(t)$ as $t \rightarrow \infty$, then, $(1/\lambda) \int^{L -1(\lambda t)}_0 f(X_s) ds$ converges to $\ell(M^{-1}(t), 0)$ as $\lambda \rightarrow \infty$, in the sense of the convergence of all finite-dimensional marginal distributions.

Citation

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Yuji Kasahara. "A Limit Theorem for Slowly Increasing Occupation Times." Ann. Probab. 10 (3) 728 - 736, August, 1982. https://doi.org/10.1214/aop/1176993780

Information

Published: August, 1982
First available in Project Euclid: 19 April 2007

zbMATH: 0492.60077
MathSciNet: MR659541
Digital Object Identifier: 10.1214/aop/1176993780

Subjects:
Primary: 60J55

Keywords: Brownian motion , Cauchy process , exponential distribution , Local time , Occupation times

Rights: Copyright © 1982 Institute of Mathematical Statistics

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Vol.10 • No. 3 • August, 1982
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