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.
Authors
- Maria Luísa Rocha (ORCID: https://orcid.org/0000-0001-9966-2271)
- Dínis Pestana (ORCID: https://orcid.org/0000-0001-8999-1354)
- Sandra Mendonça (ORCID: https://orcid.org/0000-0003-3364-0357)
- António Alberto Oliveira
Institutions
- 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)
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
Funders
- Universidade dos Açores
- Fundação para a Ciência e a Tecnologia