Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
144 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
46 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

A functional limit theorem for random processes with immigration in the case of heavy tails (1707.00829v1)

Published 4 Jul 2017 in math.PR

Abstract: Let $(X_k,\xi_k){k\in \mathbb {N}}$ be a sequence of independent copies of a pair $(X,\xi)$ where $X$ is a random process with paths in the Skorokhod space $D[0,\infty)$ and $\xi$ is a positive random variable. The random process with immigration $(Y(u)){u\in \mathbb {R}}$ is defined as the a.s. finite sum $Y(u)=\sum_{k\geq0}X_{k+1}(u- \xi_1-\cdots-\xi_k)1\mkern-4.5mu\mathrm{l}{{\xi_1+\cdots+\xi_k\leq u}}$. We obtain a functional limit theorem for the process $(Y(ut)){u\geq 0}$, as $t\to\infty$, when the law of $\xi$ belongs to the domain of attraction of an $\alpha$-stable law with $\alpha\in(0,1)$, and the process $X$ oscillates moderately around its mean $\mathbb{E}[X(t)]$. In this situation the process $(Y(ut))_{u\geq0}$, when scaled appropriately, converges weakly in the Skorokhod space $D(0,\infty)$ to a fractionally integrated inverse stable subordinator.

Summary

We haven't generated a summary for this paper yet.