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This article is cited in 7 scientific papers (total in 7 papers)
Convergence rate estimates in the global CLT for compound mixed Poisson distributions
I. G. Shevtsovaabc a Zhejiang Sci-tech University
b Federal Research Center "Computer Science and Control" of Russian Academy of Sciences, Moscow
c Lomonosov Moscow State University, Faculty of Computational Mathematics and Cybernetics
Abstract:
Using the estimates of the accuracy of the normal approximation to distributions
of Poisson-binomial random sums
from [I. G. Shevtsova, Theory Probab. Appl., 62 (2018), pp. 278–294],
we obtain moment-type estimates of the rate of convergence in the central limit
theorem for Poisson and mixed Poisson random sums in the uniform and mean
metrics.
As corollaries, we provide estimates of the accuracy of the approximation to
distributions of negative binomial random sums by the
normal law (with the growth of the shape parameter) and by the variance-gamma
mixture of the normal law
(as the “success probability” tends to zero); in particular, we present
estimates of the accuracy of the Laplace
approximation to distributions of geometric random sums.
Keywords:
Poisson random sum, geometric random sum, compound Poisson distribution, central limit theorem (CLT), convergence rate estimate, normal approximation, Laplace distribution, Berry–Esseen inequality, asymptotically exact constant.
Received: 13.05.2017 Accepted: 22.06.2017
Citation:
I. G. Shevtsova, “Convergence rate estimates in the global CLT for compound mixed Poisson distributions”, Teor. Veroyatnost. i Primenen., 63:1 (2018), 89–116; Theory Probab. Appl., 63:1 (2018), 72–93
Linking options:
https://www.mathnet.ru/eng/tvp5143https://doi.org/10.4213/tvp5143 https://www.mathnet.ru/eng/tvp/v63/i1/p89
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Abstract page: | 611 | Full-text PDF : | 88 | References: | 77 | First page: | 30 |
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