Asymptotics of random processes with immigration I: scaling limits

preprint2015arXivOpen access

Abstract

Let (X1,ξ1),(X2,ξ2),…(X_1, ξ_1), (X_2,ξ_2),\ldots be i.i.d.~copies of a pair (X,ξ)(X,ξ) where XX is a random process with paths in the Skorokhod space D[0,∞)D[0,\infty) and ξξ is a positive random variable. Define Sk:=ξ1+…+ξkS_k := ξ_1+\ldots+ξ_k, k∈N0k \in \mathbb{N}_0 and Y(t):=∑k≥0Xk+1(t−Sk)1{Sk≤t}Y(t) := \sum_{k\geq 0} X_{k+1}(t-S_k) 1_{\{S_k \leq t\}}, t≥0t\geq 0. We call the process (Y(t))t≥0(Y(t))_{t \geq 0} random process with immigration at the epochs of a renewal process. We investigate weak convergence of the finite-dimensional distributions of (Y(ut))u>0(Y(ut))_{u>0} as t→∞t\to\infty. Under the assumptions that the covariance function of XX is regularly varying in (0,∞)×(0,∞)(0,\infty)\times (0,\infty) in a uniform way, the class of limiting processes is rather rich and includes Gaussian processes with explicitly given covariance functions, fractionally integrated stable Lévy motions and their sums when the law of ξξ belongs to the domain of attraction of a stable law with finite mean, and conditionally Gaussian processes with explicitly given (conditional) covariance functions, fractionally integrated inverse stable subordinators and their sums when the law of ξξ belongs to the domain of attraction of a stable law with infinite mean.

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