Free PDF An Introduction to Copulas (Springer Series in Statistics)
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An Introduction to Copulas (Springer Series in Statistics)
Free PDF An Introduction to Copulas (Springer Series in Statistics)
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Review
From the reviews of the second edition: "This introductory and informative text on copulas is clearly written and from an educational standpoint will presented. With more than a hundred examples and over 160 exercise, this book is suitable as a textbook or for self-study. The only prerequisite is an upper level undergraduate course in probability and mathematical statistics. The second edition maintains the basic organizing of the material and the general level of presentation as the first one from 1999. The major additions are sections on: copula transformation methods; extreme value copulas; copulas with specific analytic or functional properties; tail dependence and quasi-copulas. " (Piotr Jaworski, Zentrablatt MATH, 2009, 1152) "This introductory and informative text on copulas … is clearly written and from an educational standpoint well presented. … 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. … many will be pleased to have a copy of this new text in their personal library … ." (Radu Theodorescu, Mathematical Reviews, 2006 i)
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From the Back Cover
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 116 examples, 54 figures, and 167 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. The revised second edition includes new sections on extreme value copulas, tail dependence, and quasi-copulas. 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 and Proofs Without Words II: More Exercises in Visual Thinking, published by the Mathematical Association of America.
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Product details
Series: Springer Series in Statistics
Paperback: 288 pages
Publisher: Springer (November 19, 2010)
Language: English
ISBN-10: 1441921095
ISBN-13: 978-1441921093
Product Dimensions:
6.1 x 0.6 x 9.2 inches
Shipping Weight: 1.1 pounds (View shipping rates and policies)
Average Customer Review:
3.9 out of 5 stars
7 customer reviews
Amazon Best Sellers Rank:
#1,399,353 in Books (See Top 100 in Books)
This is very high quality and well written. In that sense, I should probably give it 4 or 5 stars. So I apologize for that. My complaint is that it doesn't give enough practical understanding and examples. It just dives right in to the thick and heavy notation and proofs! In other words, a little merciful watering down (especially for the first few key concepts) couldn't have hurt.I do not recommend it for a professional who is learning how to model data correlation at work. This book is too harsh for self study.I do recommend it for an academic setting. An enthusiastic professor could help teach the concepts, and then assign problems for homework. This would even be appropriate at the undergrad level for a higher level course.
Text that explains the theory behind Copulas. This statistical tool made millions in stock market
Brace yourselves for thorough mathematical proofs. Nonetheless, great introduction into the topic.
As expected, the reference on copulas is very technical. Demands some skills on statistics (statistical mathematics, calculus, probability and inference).
I just got this book, so I can't comment on the contents yet. However, I feel quite ripped off, because this is the previous edition. The hardcover, which is only $20 more is a new second edition, while the paperback is from 1999.
This may be good as a mathematical treatise, but as a practitioner, I did not find it at all helpful.
This is the second edition of THE book on copulas; there are others, eg Joe, and Drouet and Kotz, but this is the best reference work I know of on this topic. The second edition does not frankly have a huge amount of new content; the most obvious is the very useful set of scatterplots used to illustrate the appearance of copulas. This I think shows up some properties like symmetry better than equations could do. If I had purchased the first edition, I probably wouldn't feel it had been worth upgrading---it depends on how deeply you are `into' this topic. On the other hand it's reassuring that there hasn't been a lot of recent work we didn't know about!I thoroughly recommend this book, and, if I meet the author, I shall reckon that he owes me a drink.
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