An introduction to copulas

By:

Nelsen, Roger B

Material type: Text

TextSeries: Springer Series in StatisticsPublication details: London Springer 2012Edition: 2nd edDescription: 225 pISBN:

9781441921093

Subject(s):

DDC classification:

519.535 N3I6

Summary: 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. (https://www.springer.com/in/book/9780387286594)

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Item type	Current library	Collection	Call number	Status	Date due	Barcode	Item holds
Book	Nagpur General Stacks	Non-fiction	519.535 N3I6 (Browse shelf(Opens below))	Available		IIMN-001336

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Previous	519.535 J6A7 Applied multivariate statistical analysis	519.535 L5A2 Analyzing multivariate data	519.535 L5A2-1 Analyzing multivariate data	519.535 N3I6 An introduction to copulas	519.544 W3G8 Guesstimation: solving the world's problems on the back of a cocktail napkin	519.55 B7T4 Time series: theory and methods	519.55 H2F6 Forecasting, structural time series models and the kalman filter	Next

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. (https://www.springer.com/in/book/9780387286594)

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