Discrete Multivariate Distributions is the only comprehensive, single–source reference for this increasingly important statistical subdiscipline. It covers all significant advances that have occurred in the field over the past quarter century in the theory, methodology, computational procedures, and applications of discrete multivariate distributions in a wide range of disciplines. Distributions covered include multinomial, binomial, negative binomial, Poisson, power series, hypergeometric, Pólya–Eggenberger, Ewens, orders, and some families of distributions. Each distribution is presented in its own chapter, along with necessary details and descriptions of real–world applications gleaned from the current literature on discrete multivariate distributions.
Discrete Multivariate Distributions is the fourth volume of the ongoing revision of Johnson and Kotz′s acclaimed Distributions in Statistics universally acknowledged to be the definitive work on statistical distributions. Originally planned as a revision of Chapter 11 of that classic, this project soon blossomed into a substantial volume as a result of the unprecedented growth that has occurred in the literature on discrete multivariate distributions and their applications over the past quarter century.
The only comprehensive, single–volume work on the subject, this valuable reference affords statisticians direct access to all of the latest developments concerning discrete multivariate distributions. Concentrating primarily on areas of interest to theoretical as well as applied statisticians, the authors provide complete coverage of several important discrete multivariate distributions. These include multinomial, binomial, negative binomial, Poisson, power series, hypergeometric, Pólya–Eggenberger, Ewens, orders, and some families of distributions.
Discrete Multivariate Distributions begins with a general overview of the multivariate method in which the authors lay the basic theoretical groundwork for the discussions that follow. For clarity and consistency, subsequent chapters follow a similar format, beginning with a concise historical account followed by a discussion of properties and characteristics. Coverage then advances to in–depth explorations of inferential issues and applications, liberally supplemented with helpful details and a collection of real–world applications obtained from the authors′ extensive searches of current literature worldwide.
Discrete Multivariate Distributions is an essential working resource for researchers, professionals, practitioners, and graduate students in statistics, mathematics, computer science, engineering, medicine, and the biological sciences.
Negative Multinominal and Other Multinominal–Related Distributions.
Multivariate Poisson Distributions.
Multivariate Power Series Distributions.
Multivariate Hypergeometric and Related Distributions.
Multivariate Polya–Eggenberger Distributions.
Multivariate Ewens Distribution.
Multivariate Distributions of Order s.