Asymptotic exponentiality of the distribution of first exit times for a class of markov processes with applications to quickest change detection?

We consider the first exit time of a nonnegative Harris-recurrent Markov process from the interval [0, A] as A ? ?. We provide an alternative method of proof of asymptotic exponentiality of the first exit time (suitably standardized) that does not rely on embedding in a regeneration process. We show that under certain conditions the moment generating function of a suitably standardized version of the first exit time converges to that of Exponential(1), and we connect between the standardizing constant and the quasi-stationary distribution (assuming it exists). The results are applied to the evaluation of a distribution of run length to false alarm in change-point detection problems.