Exact asymptotics of supremum of a stationary Gaussian process over a random interval

Abstract: Let ${X(t) : t \in [0, \infty) }$ be a centered stationary Gaussian process. We study the exact asymptotics of $\pr (\sup_{s \in [0,T]} X(t) > u)$, as $u \to \infty$, where $T$ is an independent of {X(t)} nonnegative random variable. It appears that the heaviness of $T$ impacts the form of the asymptotics, leading to three scenarios: the case of integrable $T$, the case of $T$ having regularly varying tail distribution with parameter $\lambda\in(0,1)$ and the case of $T$ having slowly varying tail distribution.