This book introduces a new representation of probability measures, the lift zonoid representation, and demonstrates its usefulness in statistical applica tions. The material divides into nine chapters. Chapter 1 exhibits the main idea of the lift zonoid representation and surveys the principal results of later chap ters without proofs. Chapter 2 provides a thorough investigation into the theory of the lift zonoid. All principal properties of the lift zonoid are col lected here for later reference. The remaining chapters present applications of the lift zonoid approach to various fields of multivariate analysis. Chap ter 3 introduces a family of central regions, the zonoid trimmed regions, by which a distribution is characterized. Its sample version proves to be useful in describing data. Chapter 4 is devoted to a new notion of data depth, zonoid depth, which has applications in data analysis as well as in inference. In Chapter 5 nonparametric multivariate tests for location and scale are in vestigated; their test statistics are based on notions of data depth, including the zonoid depth. Chapter 6 introduces the depth of a hyperplane and tests which are built on it. Chapter 7 is about volume statistics, the volume of the lift zonoid and the volumes of zonoid trimmed regions; they serve as multivariate measures of dispersion and dependency. Chapter 8 treats the lift zonoid order, which is a stochastic order to compare distributions for their dispersion, and also indices and related orderings.
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Karl Mosler hat Mathematik und Statistik an den Universitäten Heidelberg und München studiert sowie an der Technischen Universität München promoviert. Er lehrte Statistik und Operations Research, u.a. in Hamburg und Frankfurt/Oder. 1995 erhielt er die Professur für Statistik und Ökonometrie an der Universität zu Köln. Rainer Dyckerhoff hat an der Technischen Universität Darmstadt Mathematik studiert. Nach seiner Promotion zum Dr. rer. pol. an der Helmut-Schmidt-Universität Hamburg wechselte er 1995 an die Universität zu Köln, wo er, seit 2013 als apl. Professor, Statistik und Mathematik lehrt. Christoph Scheicher hat an der Universität Siegen Wirtschaftsmathematik studiert. 2009 promovierte er an der Universität zu Köln und lehrt dort seit 2007 u.a. Mathematische Methoden für Ökonomen.
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces a new representation of probability measures, the lift zonoid representation, and demonstrates its usefulness in statistical applica tions. The material divides into nine chapters. Chapter 1 exhibits the main idea of the lift zonoid representation and surveys the principal results of later chap ters without proofs. Chapter 2 provides a thorough investigation into the theory of the lift zonoid. All principal properties of the lift zonoid are col lected here for later reference. The remaining chapters present applications of the lift zonoid approach to various fields of multivariate analysis. Chap ter 3 introduces a family of central regions, the zonoid trimmed regions, by which a distribution is characterized. Its sample version proves to be useful in describing data. Chapter 4 is devoted to a new notion of data depth, zonoid depth, which has applications in data analysis as well as in inference. In Chapter 5 nonparametric multivariate tests for location and scale are in vestigated; their test statistics are based on notions of data depth, including the zonoid depth. Chapter 6 introduces the depth of a hyperplane and tests which are built on it. Chapter 7 is about volume statistics, the volume of the lift zonoid and the volumes of zonoid trimmed regions; they serve as multivariate measures of dispersion and dependency. Chapter 8 treats the lift zonoid order, which is a stochastic order to compare distributions for their dispersion, and also indices and related orderings. Artikel-Nr. 9780387954127
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