Conway-Maxwell-Poisson Distribution

"This is the first comprehensive introduction to the Conway-Maxwell-Poisson distribution and its contributions in statistical theory and computing in R, including its uses in count data modelling. An essential reference for academics in statistics and data science, as well as quantitative researchers and data analysts in applied disciplines"--

List of contents

Preface; 1. Introduction: count data containing dispersion; 2. The Conway-Maxwell-Poisson (COM-Poisson) distribution; 3. Distributional extensions and generalities; 4. Multivariate forms of the COM-Poisson distribution; 5. COM-Poisson regression; 6. COM-Poisson control charts; 7. COM-Poisson models for serially dependent count data; 8. COM-Poisson cure rate models; Bibliography; Index.

About the author

Kimberly F. Sellers is Professor in the Department of Mathematics and Statistics at Georgetown University, and a Principal Researcher with the Center for Statistical Research and Methodology at the US Census Bureau in Washington, DC. She is a Fellow of the American Statistical Association and an Elected Member of the International Statistical Institute.

Summary

This is the first comprehensive introduction to the Conway-Maxwell-Poisson distribution and its contributions in statistical theory and computing in R, including its uses in count data modelling. An essential reference for academics in statistics and data science, as well as quantitative researchers and data analysts in applied disciplines.

Product details

• Authors: Kimberly F Sellers, Kimberly F. Sellers, Kimberly F. (Georgetown University Sellers
• Publisher: Cambridge University Press ELT
• Languages: English
• Product format: Hardback
• Released: 01.05.2023
• EAN: 9781108481106
• ISBN: 978-1-108-48110-6
• No. of pages: 250
• Series: Institute of Mathematical Stat; Institute of Mathematical Statistics Monographs
• Subjects: Natural sciences, medicine, IT, technology > Medicine > General; Epidemiology & medical statistics, MATHEMATICS / Probability & Statistics / General, Probability & statistics, Probability and statistics, Epidemiology and Medical statistics