New Exponential Dispersion Models for Count Data-a Review and Applications

Shaul K. Bar-Lev, Ad Ridder

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

This chapter describes a methodology of constructing probability distributions on the nonnegative integers (aka counting distributions). Counting distributions have historic roots as they have been studied since the beginning of Probability Theory. The reason is their statistical importance and applicability in almost all societal and scientific areas. The methodology is based on considering natural exponential families of probability distributions. These families are uniquely determined by their variance functions. Then, counting distributions can be constructed from variance functions that show some regularity conditions. The counting distributions in this chapter are constructed from polynomial variance functions with degree at most three and from two generalizations of these. The usability of these new counting distributions is exhibited by various applications of data fitting, mortality projection, and insurance risk modeling.

Original languageEnglish
Title of host publicationStatistical Methods and Applications in Systems Assurance and Quality
PublisherCRC Press
Pages245-266
Number of pages22
ISBN (Electronic)9781040413234
ISBN (Print)9781032664040
DOIs
StatePublished - 1 Jan 2025
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2026 selection and editorial matter, Sotiris Bersimis, Polychronis Economou, and Athanasios Rakitzis; individual chapters, the contributors.

ASJC Scopus subject areas

  • General Arts and Humanities
  • General Social Sciences
  • General Business, Management and Accounting
  • General Medicine
  • General Mathematics
  • General Engineering

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