Asymptotic Exponentiality of First Exit Times for Recurrent Markov Processes and Applications to Changepoint Detection
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چکیده
We study asymptotic properties (as A →∞) of the first exit time from the interval [0, A] of a non-negative Harris-recurrent Markov process. It is shown that under certain fairly general conditions the limiting distribution of the suitably normalized first exit time is exponential E(1) and that the moment generating function converges to that of E(1). The method of proof is based on considering the quasi-stationary distribution and its relation to the normalizing factor. The results are applied to the evaluation of a distribution of run length to false alarm and local false alarm probabilities of CUSUM and Shiryaev-Roberts changepoint detection procedures.
منابع مشابه
Asymptotic Exponentiality of the Distribution of First Exit times for a Class of Markov Processes with Applications to Quickest Change Detection
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تاریخ انتشار 2008