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Zh. Vychisl. Mat. Mat. Fiz., 2010, Volume 50, Number 1, Pages 16–23 (Mi zvmmf4808)  

This article is cited in 5 scientific papers (total in 5 papers)

New algorithms for the statistical modeling of inhomogeneous Poisson ensembles

T. A. Averina

Institute of Computational Mathematics and Mathematical Geophysics, Siberian Branch of the Russian Academy of Sciences, pr. Akademika Lavrent'eva 6, Novosibirsk, 630090 Russia

Abstract: New algorithms for statistical modeling of inhomogeneous Poisson ensembles are proposed. They are based on a special method for modeling discrete random variables. The corresponding modification of the well-known maximum cross section method is developed.

Key words: inhomogeneous Poisson ensemble, Monte Carlo method, rejection algorithm, modification of the maximum cross section method.

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English version:
Computational Mathematics and Mathematical Physics, 2010, 50:1, 12–18

Bibliographic databases:

UDC: 519.676
Received: 29.05.2009
Revised: 22.06.2009

Citation: T. A. Averina, “New algorithms for the statistical modeling of inhomogeneous Poisson ensembles”, Zh. Vychisl. Mat. Mat. Fiz., 50:1 (2010), 16–23; Comput. Math. Math. Phys., 50:1 (2010), 12–18

Citation in format AMSBIB
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    Citing articles on Google Scholar: Russian citations, English citations
    Related articles on Google Scholar: Russian articles, English articles

    This publication is cited in the following articles:
    1. T. A. Averina, G. A. Mikhaǐlov, “Algorithms for the exact and approximate statistical modeling of Poisson ensembles”, Comput. Math. Math. Phys., 50:6 (2010), 951–962  mathnet  crossref  mathscinet  adsnasa  isi
    2. T. A. Averina, “A modified algorithm for statistical simulation of multistructural systems with distributed change of structure”, Num. Anal. Appl., 6:2 (2013), 91–97  mathnet  crossref  mathscinet  elib
    3. K. A. Rybakov, “An approximate solution of the optimal nonlinear filtering problem for stochastic differential systems by statistical modeling”, Num. Anal. Appl., 6:4 (2013), 324–336  mathnet  crossref  mathscinet  elib
    4. T. A. Averina, “Using a randomized method of a maximum cross-section for simulating random structure systems with distributed transitions”, Num. Anal. Appl., 9:3 (2016), 179–190  mathnet  crossref  crossref  mathscinet  isi  elib  elib
    5. T. A. Averina, K. A. Rybakov, “An approximate solution of the prediction problem for stochastic jump-diffusion systems”, Num. Anal. Appl., 10:1 (2017), 1–10  mathnet  crossref  crossref  mathscinet  isi  elib
  • Журнал вычислительной математики и математической физики Computational Mathematics and Mathematical Physics
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