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Teoriya Veroyatnostei i ee Primeneniya, 1969, Volume 14, Issue 2, Pages 348–354 (Mi tvp1182)  

This article is cited in 2 scientific papers (total in 2 papers)

Short Communications

Some explicit formulas in the theory of branching stochastic processes with discrete time and one-type particles

B. I. Selivanov

Moscow
Full-text PDF (407 kB) Citations (2)
Abstract: Let $Z_0=1$, $Z_n$, $n=1,2,\dots,$ be the number of particles belonging to the $n$-th generation of a Halton–Watson branching process, $p_{nr}=\mathbf P\{Z_n=r\}$ and $F_n(z)=\sum_{r\ge0}p_{nr}z^r$. It is supposed that $m=\mathbf EZ_1\ne1$ and $F(z)=F_1(z)$ be regular at the point $z=1$ for $m<1$. In the paper some formulas and an asymptotic expansion for the probabilities $p_{nr}$ are obtained.
Received: 18.04.1967
Revised: 24.01.1968
English version:
Theory of Probability and its Applications, 1969, Volume 14, Issue 2, Pages 336–342
DOI: https://doi.org/10.1137/1114043
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: B. I. Selivanov, “Some explicit formulas in the theory of branching stochastic processes with discrete time and one-type particles”, Teor. Veroyatnost. i Primenen., 14:2 (1969), 348–354; Theory Probab. Appl., 14:2 (1969), 336–342
Citation in format AMSBIB
\Bibitem{Sel69}
\by B.~I.~Selivanov
\paper Some explicit formulas in the theory of branching stochastic processes with discrete time and one-type particles
\jour Teor. Veroyatnost. i Primenen.
\yr 1969
\vol 14
\issue 2
\pages 348--354
\mathnet{http://mi.mathnet.ru/tvp1182}
\mathscinet{http://mathscinet.ams.org/mathscinet-getitem?mr=246378}
\zmath{https://zbmath.org/?q=an:0281.60100|0214.16301}
\transl
\jour Theory Probab. Appl.
\yr 1969
\vol 14
\issue 2
\pages 336--342
\crossref{https://doi.org/10.1137/1114043}
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  • This publication is cited in the following 2 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Теория вероятностей и ее применения Theory of Probability and its Applications
     
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