Discrete Multivariate Distributions

Timely, comprehensive, practical--an important working resource forall who use this critical statistical method

Discrete Multivariate Distributions is the only comprehensive,single-source reference for this increasingly important statisticalsubdiscipline. It covers all significant advances that haveoccurred in the field over the past quarter century in the theory,methodology, computational procedures, and applications of discretemultivariate distributions in a wide range of disciplines.Distributions covered include multinomial, binomial, negativebinomial, Poisson, power series, hypergeometric, Polya-Eggenberger,Ewens, orders, and some families of distributions. Eachdistribution is presented in its own chapter, along with necessarydetails and descriptions of real-world applications gleaned fromthe current literature on discrete multivariatedistributions.

Discrete Multivariate Distributions is the fourth volume of theongoing revision of Johnson and Kotz's acclaimed Distributions inStatistics--universally acknowledged to be the definitive work onstatistical distributions. Originally planned as a revision ofChapter 11 of that classic, this project soon blossomed into asubstantial volume as a result of the unprecedented growth that hasoccurred in the literature on discrete multivariate distributionsand their applications over the past quarter century.

The only comprehensive, single-volume work on the subject, thisvaluable reference affords statisticians direct access to all ofthe latest developments concerning discrete multivariatedistributions. Concentrating primarily on areas of interest totheoretical as well as applied statisticians, the authors providecomplete coverage of several important discrete multivariatedistributions. These include multinomial, binomial, negativebinomial, Poisson, power series, hypergeometric, Polya-Eggenberger,Ewens, orders, and some families of distributions.

Discrete Multivariate Distributions begins with a general overviewof the multivariate method in which the authors lay the basictheoretical groundwork for the discussions that follow. For clarityand consistency, subsequent chapters follow a similar format,beginning with a concise historical account followed by adiscussion of properties and characteristics. Coverage thenadvances to in-depth explorations of inferential issues andapplications, liberally supplemented with helpful details and acollection of real-world applications obtained from the authors'extensive searches of current literature worldwide.

Discrete Multivariate Distributions is an essential workingresource for researchers, professionals, practitioners, andgraduate students in statistics, mathematics, computer science,engineering, medicine, and the biological sciences.

NORMAN L. JOHNSON, PhD, DSc, is Professor Emeritus in theDepartment of Statistics at the University of North Carolina atChapel Hill. Dr. Johnson received his PhD and DSc degrees instatistics from the University of London, and has taught atUniversity College, London, the Case Institute of Technology, andthe University of New South Wales. He is coauthor of UnivariateDiscrete Distributions, Second Edition (with Samuel Kotz andAdrienne W. Kemp), and Continuous Univariate Distributions, Volumes1 and 2, Second Edition (with Samuel Kotz and N. Balakrishnan). Dr.Johnson was Editor in Chief (with Samuel Kotz) of the ten-volumeEncyclopedia of Statistical Sciences, and he is currently AssociateEditor of Metron and a member of the editorial board of SequentialAnalysis.

SAMUEL KOTZ, PhD, is Professor of Statistics in the Department ofManagement Science and Statistics at the University of Maryland atCollege Park. Dr. Kotz received his PhD in mathematical statisticsfrom Cornell University and has held distinguished visitingpositions at Bucknell University, Bowling Green State University,Tel Aviv University, University of Guelph, Harbin Institute ofTechnology (China), and Lule? University (Sweden). He is thecoauthor of Urn Models and Applications, Symmetric Multivariate andRelated Distributions, Educated Guessing, and Process CapabilityIndices. He is Coordinating Editor of Journal of StatisticalPlanning and Inference.

N. BALAKRISHNAN, PhD, is Professor in the Department of Mathematicsand Statistics at McMaster University, Hamilton, Ontario, Canada.In addition to publishing many research papers, he has authored orcoauthored numerous books, including A First Course in OrderStatistics 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, NavalResearch Logistics Quarterly, IIE Transactions, American Journal ofMathematical and Management Sciences, and Journal of AppliedStatistical Science.