Foss, Sergey, Korshunov, Dmitry, Palmowski, Zbigniew
{"title":"Branching processes with immigration in atypical random environment","authors":"Foss, Sergey, Korshunov, Dmitry, Palmowski, Zbigniew","doi":"10.1007/s10687-021-00427-1","DOIUrl":null,"url":null,"abstract":"<p>Motivated by a seminal paper of Kesten et al. (<i>Ann. Probab.</i>, <i>3(1)</i>, 1–31, 1975) we consider a branching process with a conditional geometric offspring distribution with i.i.d. random environmental parameters <i>A</i><sub><i>n</i></sub>, <i>n</i> ≥ 1 and with one immigrant in each generation. In contrast to above mentioned paper we assume that the environment is long-tailed, that is that the distribution <i>F</i> of <span>\\(\\xi _{n}:=\\log ((1-A_{n})/A_{n})\\)</span> is long-tailed. We prove that although the offspring distribution is light-tailed, the environment itself can produce extremely heavy tails of the distribution of the population size in the <i>n</i> th generation which becomes even heavier with increase of <i>n</i>. More precisely, we prove that, for all <i>n</i>, the distribution tail <span>\\(\\mathbb {P}(Z_{n} \\ge m)\\)</span> of the <i>n</i> th population size <i>Z</i><sub><i>n</i></sub> is asymptotically equivalent to <span>\\(n\\overline F(\\log m)\\)</span> as <i>m</i> grows. In this way we generalise Bhattacharya and Palmowski (<i>Stat. Probab. Lett.</i>, <i>154</i>, 108550, 2019) who proved this result in the case <i>n</i> = 1 for regularly varying environment <i>F</i> with parameter <i>α</i> > 1. Further, for a subcritical branching process with subexponentially distributed <i>ξ</i><sub><i>n</i></sub>, we provide the asymptotics for the distribution tail <span>\\(\\mathbb {P}(Z_{n}>m)\\)</span> which are valid uniformly for all <i>n</i>, and also for the stationary tail distribution. Then we establish the “principle of a single atypical environment” which says that the main cause for the number of particles to be large is the presence of a single very small environmental parameter <i>A</i><sub><i>k</i></sub>.</p>","PeriodicalId":49274,"journal":{"name":"Extremes","volume":"34 1","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2021-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Extremes","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s10687-021-00427-1","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Motivated by a seminal paper of Kesten et al. (Ann. Probab., 3(1), 1–31, 1975) we consider a branching process with a conditional geometric offspring distribution with i.i.d. random environmental parameters An, n ≥ 1 and with one immigrant in each generation. In contrast to above mentioned paper we assume that the environment is long-tailed, that is that the distribution F of \(\xi _{n}:=\log ((1-A_{n})/A_{n})\) is long-tailed. We prove that although the offspring distribution is light-tailed, the environment itself can produce extremely heavy tails of the distribution of the population size in the n th generation which becomes even heavier with increase of n. More precisely, we prove that, for all n, the distribution tail \(\mathbb {P}(Z_{n} \ge m)\) of the n th population size Zn is asymptotically equivalent to \(n\overline F(\log m)\) as m grows. In this way we generalise Bhattacharya and Palmowski (Stat. Probab. Lett., 154, 108550, 2019) who proved this result in the case n = 1 for regularly varying environment F with parameter α > 1. Further, for a subcritical branching process with subexponentially distributed ξn, we provide the asymptotics for the distribution tail \(\mathbb {P}(Z_{n}>m)\) which are valid uniformly for all n, and also for the stationary tail distribution. Then we establish the “principle of a single atypical environment” which says that the main cause for the number of particles to be large is the presence of a single very small environmental parameter Ak.
ExtremesMATHEMATICS, INTERDISCIPLINARY APPLICATIONS-STATISTICS & PROBABILITY
CiteScore
2.20
自引率
7.70%
发文量
15
审稿时长
>12 weeks
期刊介绍:
Extremes publishes original research on all aspects of statistical extreme value theory and its applications in science, engineering, economics and other fields. Authoritative and timely reviews of theoretical advances and of extreme value methods and problems in important applied areas, including detailed case studies, are welcome and will be a regular feature. All papers are refereed. Publication will be swift: in particular electronic submission and correspondence is encouraged.
Statistical extreme value methods encompass a very wide range of problems: Extreme waves, rainfall, and floods are of basic importance in oceanography and hydrology, as are high windspeeds and extreme temperatures in meteorology and catastrophic claims in insurance. The waveforms and extremes of random loads determine lifelengths in structural safety, corrosion and metal fatigue.