Predicting extinction or explosion in a Galton–Watson branching process

Peter Guttorp () and Michael Perlman ()

Statistical Inference for Stochastic Processes, 2013, vol. 16, issue 2, 113-125

Abstract: Based on observations $$X_1,\dots ,X_n$$ X 1 , … , X n of successive generations of a discrete-parameter Galton–Watson branching process, one wishes to predict whether extinction or explosion will ultimately occur. This problem can be formulated as a simple hypothesis-testing problem to which the Neyman–Pearson Lemma is directly applicable if the extinction probability is known or estimable. If it is not, valid (but conservative) tests still can be obtained. Copyright Springer Science+Business Media Dordrecht 2013

Keywords: Hypothesis testing; Likelihood ratio; Universal test; Criticality (search for similar items in EconPapers)
Date: 2013
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1007/s11203-013-9083-0 (text/html)
Access to full text is restricted to subscribers.

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:spr:sistpr:v:16:y:2013:i:2:p:113-125

Ordering information: This journal article can be ordered from
http://www.springer. ... ty/journal/11203/PS2

DOI: 10.1007/s11203-013-9083-0

Access Statistics for this article

Statistical Inference for Stochastic Processes is currently edited by Denis Bosq, Yury A. Kutoyants and Marc Hallin

More articles in Statistical Inference for Stochastic Processes from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().