Branching processes with immigration in atypical random environment

Sergey Foss, Dmitry Korshunov, Zbigniew Palmowski*

*Corresponding author for this work

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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 ξn: = log((1 − An) / An) 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 ℙ(Zn≥ m) of the n th population size Zn is asymptotically equivalent to nF¯ (logm) 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 ℙ(Zn> 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.

Original languageEnglish
Pages (from-to)55–77
Number of pages23
JournalExtremes
Volume25
Early online date20 Sept 2021
DOIs
Publication statusPublished - Mar 2022

Keywords

  • Branching process
  • Random environment
  • Random walk in random environment
  • Slowly varying distribution
  • Subexponential distribution

ASJC Scopus subject areas

  • Statistics and Probability
  • Engineering (miscellaneous)
  • Economics, Econometrics and Finance (miscellaneous)

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