Convergence and inference for mixed Poisson random sums

Gabriela Oliveira (), Wagner Barreto-Souza () and Roger W. C. Silva ()
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Gabriela Oliveira: Universidade Federal de Minas Gerais
Wagner Barreto-Souza: Universidade Federal de Minas Gerais
Roger W. C. Silva: Universidade Federal de Minas Gerais

Metrika: International Journal for Theoretical and Applied Statistics, 2021, vol. 84, issue 5, No 6, 777 pages

Abstract: Abstract We study the limit distribution of partial sums with a random number of terms following a class of mixed Poisson distributions. The resulting weak limit is a mixture between a normal distribution and an exponential family, which we call by normal exponential family (NEF) laws. A new stability concept is introduced and a relationship between $$\alpha $$ α -stable distributions and NEF laws is established. We propose the estimation of the NEF model parameters through the method of moments and also by the maximum likelihood method via an Expectation–Maximization algorithm. Monte Carlo simulation studies are addressed to check the performance of the proposed estimators, and an empirical illustration of the financial market is presented.

Keywords: EM-algorithm; Mixed Poisson distribution; Stability; Weak convergence; 60F05; 62E20; 62Fxx (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s00184-020-00800-3

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