Continuous Multivariate Distributions, Volume 1: Models and Applications 2nd Edition by Samuel Kotz (PDF)

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Continuous Multivariate Distributions, Volume 1, Second Edition provides a remarkably comprehensive, self-contained resource for this critical statistical area. It covers all significant advances that have occurred in the field over the past quarter century in the theory, methodology, inferential procedures, computational and simulational aspects, and applications of continuous multivariate distributions. In-depth coverage includes MV systems of distributions, MV normal, MV exponential, MV extreme value, MV beta, MV gamma, MV logistic, MV Liouville, and MV Pareto distributions, as well as MV natural exponential families, which have grown immensely since the 1970s. Each distribution is presented in its own chapter along with descriptions of real-world applications gleaned from the current literature on continuous multivariate distributions and their applications.

User’s Reviews

Editorial Reviews: Review This book brings one right up to date and is a worthy addition to the existing set of second editions of the other volumes of Distributions in Statistics. It will remain the key reference for many years. (Short Book Reviews, Vol. 20, No. 3, December 2000) […] Continuous Multivariate Distributions is a unique and valuable source of information on multivariate distributions. This book, and the rest of this venerable and important series, should be on the shelves of every statistician. (JASA June 2001) For certain it will serve as the primary source for continuous multivariate statistical distributions for a long time. (Zentralblatt Math, Volume 946, No 21, 2000) “…provides a remarkably comprehensive, self-contained resource for this important statistical area.” (Mathematical Reviews, Issue 2001h) “It will remain the key reference for many years.” (Short Book Reviews, December 2000) “…will serve as the primary source for continuous multivariate statistical distributions for a long time.” (Zentralblatt MATH, Vol. 946, No. 21) “Like its predecessors, this monograph is a most welcome addition to the statistical literature. We are looking forward to Volume 2…” (Statistical Papers, Vol. 42, No. 3, 2001) From the Inside Flap The fifth volume in what is widely known as the definitive work on statistical distributions, Continuous Multivariate Distributions, Volume 1, Second Edition is a comprehensive revision of Johnson and Kotz’s acclaimed 1972 volume. It represents the next installment in a unique collection that encompasses discrete univariate distributions, continuous univariate distributions, and discrete multivariate distributions. Presenting a comprehensive, authoritative, up-to-date treatment of continuous multivariate distributions (CMD), this volume focuses on the many ways in which multivariate (MV) distributions have been constructed, investigated, and applied over the past quarter century. It addresses advances made through the use of computers, incorporates many important results from the literature, and highlights the increasing popularity of various MV distributions for use in statistical analyses of models in applied fields. A broad range of MV distributional models is discussed in detail. This new edition does not include sampling distributions such as MV t and Wishart, but contains significantly expanded coverage of MV general systems, MV normal, MV exponential, MV extreme value, MV beta, MV gamma, MV logistic, MV Liouville, and MV Pareto distributions. In addition, a completely new chapter is devoted to MV natural exponential families, reflecting the rapid developments this new topic has seen since the 1970s. Continuous Multivariate Distributions, Volume 1, Second Edition provides a detailed description of properties for each CMD, explains inferential methods for them, and outlines their application in a variety of real-world problems and settings. It is an indispensable working resource for theoreticians in statistical methodology as well as for applied researchers in engineering, health sciences, economics, business, environmental sciences, and behavioral and social sciences. From the Back Cover Continuous Multivariate Distributions, Volume 1, Second Edition provides a remarkably comprehensive, self-contained resource for this critical statistical area. It covers all significant advances that have occurred in the field over the past quarter century in the theory, methodology, inferential procedures, computational and simulational aspects, and applications of continuous multivariate distributions. In-depth coverage includes MV systems of distributions, MV normal, MV exponential, MV extreme value, MV beta, MV gamma, MV logistic, MV Liouville, and MV Pareto distributions, as well as MV natural exponential families, which have grown immensely since the 1970s. Each distribution is presented in its own chapter along with descriptions of real-world applications gleaned from the current literature on continuous multivariate distributions and their applications. About the Author SAMUEL KOTZ, PhD, is Professor and Research Scholar at the Department of Engineering Management and Systems Engineering at George Washington University. Formerly with the University of Maryland at College Park, Dr. Kotz received his PhD 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 LuleÃ¥ University (Sweden). He is the coauthor of Urn Models and Applications, Symmetric Multivariate and Related Distributions, Educated Guessing, Process Capability Indices and Recent Advances in Information Theory. He is Editor-in-Chief and founder of the Encyclopedia of Statistical Sciences and holds three honorary doctorates. 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 Records, both of which are Wiley publications. Dr. Balakrishnan serves on the editorial board of many journals, including Journal of Statistical Planning and Inference, Computational Statistics & Data Analysis, Metrika, Methodology and Computing in Applied Probability, IIE Transactions on Quality and Reliability Engineering, and American Journal of Mathematical and Management Sciences. He is also the Editor-in-Chief f for the series Statistics for Industry and Technology and the series Statistical Distributions and Models with Applications. 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. Dr. Johnson is coauthor of the previous four volumes of this book (with Kotz and Kemp; and Kotz and Balakrishnan) and was Editor-in-Chief (with Kotz) of the ten-volume Encyclopedia of Statistical Sciences. He is currently Associate Editor of Metron and a member of the editorial board of Sequential Analysis. Read more

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