Description
Book SynopsisUnivariate Distributions.- Bivariate Copulas.- Distributions Expressed as Copulas.- Concepts of Stochastic Dependence.- Measures of Dependence.- Construction of Bivariate Distributions.- Bivariate Distributions Constructed by the Conditional Approach.- Variables-in-Common Method.- Bivariate Gamma and Related Distributions.- Simple Forms of the Bivariate Density Function.- Bivariate Exponential and Related Distributions.- Bivariate Normal Distribution.- Bivariate Extreme-Value Distributions.- Elliptically Symmetric Bivariate Distributions and Other Symmetric Distributions.- Simulation of Bivariate Observations.
Trade ReviewFrom the reviews of the second edition:
“The authors present the forms, properties, dependence structures, computation, and applications of numerous continuous bivariate distributions. … One of the nice features of this edition is that it presents bivariate distributions that are generated by a variety of copulas. … The new edition is comprised of 14 chapters including references at the end of each chapter … and subject index at the end. … I can safely recommend this book as a handy resource manual for researchers as well as practitioners working in this area.” (Technometrics, Vol. 51 (4), November, 2009)
“The book begins with a survey of univariate distributions, necessary to clarify notation in subsequent chapters. … Every time you open this volume, even at a random page, you’ll likely find something of interest. … You might well recommend it as collateral reading in a statistics class that you are teaching. As the students progress in their academic pursuits and/or in their subsequent careers, it will be a useful reference.” (Barry C. Arnold, Mathematical Reviews, Issue 2012 h)
Table of ContentsUnivariate distributions. - Bivariate copulas. - Distributions expressed as copulas. - Concepts of stochastic dependence. - Measures of dependence. - Constructions of bivariate distributions.- Bivariate distributions constructed by conditional approach. - Variables in common method. - Bivariate gamma and related distributions. - Simple forms of the bivariate density function. - Bivariate exponentional and related distributions. - Bivariate normal distribution. - Bivariate extreme value distributions. - Elliptically symmetric bivariate distributions and other symmetric distributions. - Simulation of bivariate observations.
