Count Random Variables

The observation of randomness patterns serves as guidance for the craft of probabilistic modelling. The most used count models—Binomial, Poisson, Negative Binomial—are the discrete Morris’ natural exponential families whose variance is at most quadratic on the mean, and the solutions of Katz–Panjer recurrence relation, aside from being members of the generalised power series and hypergeometric distribution families, and this accounts for their many advantageous characteristics. Some other basic count models are also described, as well as models with less obvious but useful randomness patterns in connection with maximum entropy characterisations, such as Zipf and Good models. Simple tools, such as truncation, thinning, or parameter randomisation, are straightforward ways of constructing other count models.

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Publication Details

Journal
Encyclopedia
Published
2024-09-23
DOI
https://doi.org/10.3390/encyclopedia4030089
Primary Topic
Financial Risk and Volatility Modeling
Type
article
Field-Weighted Citation Impact
0.00

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article

Count Random Variables

Maria Luísa Rocha, Dínis Pestana, Sandra Mendonça, António Alberto Oliveira
Encyclopedia
Financial Risk and Volatility Modeling
article

Count Random Variables

Maria Luísa Rocha, Dínis Pestana, Sandra Mendonça, António Alberto Oliveira
article en

Abstract

The observation of randomness patterns serves as guidance for the craft of probabilistic modelling. The most used count models—Binomial, Poisson, Negative Binomial—are the discrete Morris’ natural exponential families whose variance is at most quadratic on the mean, and the solutions of Katz–Panjer recurrence relation, aside from being members of the generalised power series and hypergeometric distribution families, and this accounts for their many advantageous characteristics. Some other basic count models are also described, as well as models with less obvious but useful randomness patterns in connection with maximum entropy characterisations, such as Zipf and Good models. Simple tools, such as truncation, thinning, or parameter randomisation, are straightforward ways of constructing other count models.

EncyclopediaVol. 4(3)
Universidade dos Açores (PT), University of Lisbon (PT), Instituto Superior de Ciencias Sociais e Relações Internacionais (AO), Instituto de Investigação Científica Tropical (PT), Universidade da Madeira (PT)
Universidade dos Açores, Fundação para a Ciência e a Tecnologia
Openalex Percentile: Top 78%
Financial Risk and Volatility Modeling
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