Research output: Contribution to journal › Article › peer-review
Branching processes with immigration in atypical random environment. / Foss, Sergey; Korshunov, Dmitry; Palmowski, Zbigniew.
In: Extremes, Vol. 25, No. 1, 03.2022, p. 55-77.Research output: Contribution to journal › Article › peer-review
}
TY - JOUR
T1 - Branching processes with immigration in atypical random environment
AU - Foss, Sergey
AU - Korshunov, Dmitry
AU - Palmowski, Zbigniew
N1 - Funding Information: The work of S Foss and D Korshunov is partially supported by the RFBR grant 19-51-53010 (2019-2020). The work of Z Palmowski is partially supported by the Polish National Science Centre under the grant 2018/29/B/ST1/00756 (2019-2022). Publisher Copyright: © 2021, The Author(s).
PY - 2022/3
Y1 - 2022/3
N2 - 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.
AB - 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.
KW - Branching process
KW - Random environment
KW - Random walk in random environment
KW - Slowly varying distribution
KW - Subexponential distribution
UR - http://www.scopus.com/inward/record.url?scp=85115186385&partnerID=8YFLogxK
U2 - 10.1007/s10687-021-00427-1
DO - 10.1007/s10687-021-00427-1
M3 - Article
AN - SCOPUS:85115186385
VL - 25
SP - 55
EP - 77
JO - Extremes
JF - Extremes
SN - 1386-1999
IS - 1
ER -
ID: 34258267