English

A renewal theorem for relatively stable variables

Probability 2020-07-29 v3

Abstract

Let F{dx}F\{dx\} be a relatively stable probability distribution on the whole real line and SnS_n the random walk started at the origin with step distribution FF. We obtain an exact asymptotic form of the Green measure U{x+dy}=n=0P[Snxdy]U\{x+dy\}= \sum_{n=0}^\infty P[S_n-x \in dy] as xx\to \infty when SnS_n is transient and SnS_n\to \infty in probability. If FF is concentrated on [0,)[0,\infty), it is relatively stable if and only if (x):=0xF{(t,)}dt\ell(x) :=\int_0^x F\{(t,\infty)\}dt is slowly varying at infinity; our result entails that if FF is non-arithmetic and relatively stable, then limx(x)U{[x,x+h)}=h\lim_{x\to\infty}\, \ell(x)U\{[x, x+h)\} = h for each h>0h>0. This surpasses the known result due to Erickson \cite{Ec}, the latter assuming the stronger condition that xF{(x,)}xF\{(x,\infty)\} is slowly varying. An obvious analog also holds for arithmetic variables.

Keywords

Cite

@article{arxiv.1911.10889,
  title  = {A renewal theorem for relatively stable variables},
  author = {Kohei Uchiyama},
  journal= {arXiv preprint arXiv:1911.10889},
  year   = {2020}
}

Comments

17 pages, to appear in Bulletin of LMS

R2 v1 2026-06-23T12:26:18.288Z