Overview

Copulas are functions that join multivariate distribution functions to their one-dimensional margins. The study of copulas and their role in statistics is a new but vigorously growing field. In this book the student or practitioner of statistics and probability will find discussions of the fundamental properties of copulas and some of their primary applications. The applications include the study of dependence and measures of association, and the construction of families of bivariate distributions. With nearly a hundred examples and over 150 exercises, this book is suitable as a text or for self-study. The only prerequisite is an upper level undergraduate course in probability and mathematical statistics, although some familiarity with nonparametric statistics would be useful. Knowledge of measure-theoretic probability is not required. Roger B. Nelsen is Professor of Mathematics at Lewis & Clark College in Portland, Oregon. He is also the author of Proofs Without Words: Exercises in Visual Thinking, published by the Mathematical Association of America.

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From the reviews of the second edition: <p> This introductory and informative text on copulas a ] is clearly written and from an educational standpoint well presented. a ] In addition to its primary use as an introductory book on copulas, this text could also serve as a complement to a graduate course or seminar in multivariate analysis focusing on dependence concepts. Readership: people interested in dependence concepts in multivariate analysis. a ] many will be pleased to have a copy of this new text in their personal library a ] . (Radu Theodorescu, Mathematical Reviews, 2006 i)

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