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An Introduction to Copulas
Taschenbuch von Roger B. Nelsen
Sprache: Englisch

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Beschreibung
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.
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.
Zusammenfassung
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.
Inhaltsverzeichnis
Definitions and Basic Properties.- Methods of Constructing Copulas.- Archimedean Copulas.- Dependence.- Additional Topics.
Details
Medium: Taschenbuch
Inhalt: xiv
272 S.
ISBN-13: 9781441921093
ISBN-10: 1441921095
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Nelsen, Roger B.
Auflage: Softcover reprint of hardcover 2nd edition 2006
Hersteller: Springer New York
Springer US, New York, N.Y.
Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com
Maße: 235 x 155 x 16 mm
Von/Mit: Roger B. Nelsen
Erscheinungsdatum: 19.11.2010
Gewicht: 0,441 kg
Artikel-ID: 107219661
Zusammenfassung
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.
Inhaltsverzeichnis
Definitions and Basic Properties.- Methods of Constructing Copulas.- Archimedean Copulas.- Dependence.- Additional Topics.
Details
Medium: Taschenbuch
Inhalt: xiv
272 S.
ISBN-13: 9781441921093
ISBN-10: 1441921095
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Nelsen, Roger B.
Auflage: Softcover reprint of hardcover 2nd edition 2006
Hersteller: Springer New York
Springer US, New York, N.Y.
Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com
Maße: 235 x 155 x 16 mm
Von/Mit: Roger B. Nelsen
Erscheinungsdatum: 19.11.2010
Gewicht: 0,441 kg
Artikel-ID: 107219661
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