Tail generating functions for extendable branching processes

Serik Sagitov

Stochastic Processes and their Applications, 2017, vol. 127, issue 5, 1649-1675

Abstract: We study branching processes of independently splitting particles in the continuous time setting. If time is calibrated such that particles live on average one unit of time, the corresponding transition rates are fully determined by the generating function f for the offspring number of a single particle. We are interested in the defective case f(1)=1−ϵ, where each splitting particle with probability ϵ is able to terminate the whole branching process. A branching process {Zt}t≥0 will be called extendable if f(q)=q and f(r)=r for some 0≤qKeywords: Markov branching process; Branching with killing; Modified linear-fractional distribution; xlogx-condition; Termination time (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304414916301545
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:spapps:v:127:y:2017:i:5:p:1649-1675

Ordering information: This journal article can be ordered from
http://http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

DOI: 10.1016/j.spa.2016.09.004

Access Statistics for this article

Stochastic Processes and their Applications is currently edited by T. Mikosch

More articles in Stochastic Processes and their Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().