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  • 标题:Large deviations for the maximum of a branching random walk with stretched exponential tails
  • 本地全文:下载
  • 作者:Piotr Dyszewski ; Nina Gantert ; Thomas Höfelsauer
  • 期刊名称:Electronic Communications in Probability
  • 印刷版ISSN:1083-589X
  • 出版年度:2020
  • 卷号:25
  • DOI:10.1214/20-ECP353
  • 语种:English
  • 出版社:Electronic Communications in Probability
  • 摘要:We prove large deviation results for the position of the rightmost particle, denoted by $M_{n}$, in a one-dimensional branching random walk in a case when Cramér’s condition is not satisfied. More precisely we consider step size distributions with stretched exponential upper and lower tails, i.e. both tails decay as $e^{-\Theta (|t|^{r})}$ for some $r\in ( 0,1)$. It is known that in this case, $M_{n}$ grows as $n^{1/r}$ and in particular faster than linearly in $n$. Our main result is a large deviation principle for the laws of $n^{-1/r}M_{n}$ . In the proof we use a comparison with the maximum of (a random number of) independent random walks, denoted by $\tilde{M} _{n}$, and we show a large deviation principle for the laws of $n^{-1/r}\tilde{M} _{n}$ as well.
  • 关键词:branching random walk;large deviations;stretched exponential random variables
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