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, Pslya-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, theauthors provide complete coverage of several important discrete multivariate distributions. These include multinomial, binomial, negative binomial, Poisson, power series, hypergeometric, Pslya-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.
General Remarks. Multinominal Distributions. 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. Miscellaneous Distributions. Abbreviations. Indexes.
NORMAN L. JOHNSON, PhD, DSc, is Professor Emeritus in the Department of Statistics at the University of North Carolina at Chapel Hill. Dr. Johnson received his PhD and DSc degrees in statistics from the University of London, and has taught at University College, London, the Case Institute of Technology, and the University of New South Wales. He is coauthor of Univariate Discrete Distributions, Second Edition (with Samuel Kotz and Adrienne W. Kemp), and Continuous Univariate Distributions, Volumes 1 and 2, Second Edition (with Samuel Kotz and N. Balakrishnan). Dr. Johnson was Editor in Chief (with Samuel Kotz) of the ten-volume Encyclopedia of Statistical Sciences, and he is currently Associate Editor of Metron and a member of the editorial board of Sequential Analysis. SAMUEL KOTZ, PhD, is Professor of Statistics in the Department of Management Science and Statistics at the University of Maryland at College Park. Dr. Kotz received his PhD in mathematical statistics from Cornell University and has held distinguished visiting positions at Bucknell University, Bowling Green State University, Tel Aviv University, University of Guelph, Harbin Institute of Technology (China), and Lule? University (Sweden). He is the coauthor of Urn Models and Applications, Symmetric Multivariate and Related Distributions, Educated Guessing, and Process Capability Indices. He is Coordinating Editor of Journal of Statistical Planning and Inference. N. BALAKRISHNAN, PhD, is Professor in the Department of Mathematics and Statistics at McMaster University, Hamilton, Ontario, Canada. In addition to publishing many research papers, he has authored or coauthored numerous books, including A First Course in Order Statistics and Order Statistics and Inference: Estimation Methods. Dr. Balakrishnan serves on the editorial board of many journals, including Communications in Statistics, Computational Statistics & Data Analysis, IEEE Transactions on Reliability, Naval Research Logistics Quarterly, IIE Transactions, American Journal of Mathematical and Management Sciences, and Journal of Applied Statistical Science.