Synopsis
Empirical process techniques for independent data have been used for many years in statistics and probability theory. This work gives an introduction to a new theory of empirical process techniques --- treating dependent data --- which has so far been scattered widely in the statistical and probabilistic literature, and surveys the most recent developments in various related fields. To date this book is the only comprehensive treatment of the topic in book literature. It is an ideal introductory text that will serve as a reference or resource for classroom use.
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Empirical Process Techniques for Dependent Data
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Empirical Process Techniques for Dependent Data
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Birkhäuser Boston Okt 2012, 2012
ISBN 10 : 1461266114
ISBN 13 : 9781461266112
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Empirical process techniques for independent data have been used for many years in statistics and probability theory. These techniques have proved very useful for studying asymptotic properties of parametric as well as non-parametric statistical procedures. Recently, the need to model the dependence structure in data sets from many different subject areas such as finance, insurance, and telecommunications has led to new developments concerning the empirical distribution function and the empirical process for dependent, mostly stationary sequences. This work gives an introduction to this new theory of empirical process techniques, which has so far been scattered in the statistical and probabilistic literature, and surveys the most recent developments in various related fields. Key features: A thorough and comprehensive introduction to the existing theory of empirical process techniques for dependent data \* Accessible surveys by leading experts of the most recent developments in various related fields \* Examines empirical process techniques for dependent data, useful for studying parametric and non-parametric statistical procedures \* Comprehensive bibliographies \* An overview of applications in various fields related to empirical processes: e.g., spectral analysis of time-series, the bootstrap for stationary sequences, extreme value theory, and the empirical process for mixing dependent observations, including the case of strong dependence. To date this book is the only comprehensive treatment of the topic in book literature. It is an ideal introductory text that will serve as a reference or resource for classroom use in the areas of statistics, time-series analysis, extreme value theory, point process theory, and applied probability theory. Contributors: P. Ango Nze, M.A. Arcones, I. Berkes, R. Dahlhaus, J. Dedecker, H.G. Dehling, 396 pp. Englisch. N° de réf. du vendeur 9781461266112
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Empirical Process Techniques for Dependent Data
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ISBN 10 : 1461266114
ISBN 13 : 9781461266112
Neuf
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Empirical process techniques for independent data have been used for many years in statistics and probability theory. These techniques have proved very useful for studying asymptotic properties of parametric as well as non-parametric statistical procedures. N° de réf. du vendeur 4189256
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Empirical Process Techniques for Dependent Data
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ISBN 13 : 9781461266112
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Empirical Process Techniques for Dependent Data
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Taschenbuch. Etat : Neu. Empirical Process Techniques for Dependent Data | Herold Dehling (u. a.) | Taschenbuch | xi | Englisch | 2012 | Birkhäuser | EAN 9781461266112 | Verantwortliche Person für die EU: Springer Basel AG in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. N° de réf. du vendeur 106029441
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Empirical Process Techniques for Dependent Data
Edité par
Birkhäuser Boston, Birkhäuser Boston Okt 2012, 2012
ISBN 10 : 1461266114
ISBN 13 : 9781461266112
Neuf
Taschenbuch
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Empirical process techniques for independent data have been usedfor many years in statistics and probability theory. These techniqueshave proved very useful for studying asymptotic properties ofparametric as well as non-parametric statistical procedures. Recentlythe need to model the dependence structure in data sets from manydifferent subject areas such as finance, insurance, andtelecommunications has led to new developments concerning theempirical distribution function and the empirical process fordependent, mostly stationary sequences. This work gives anintroduction to this new theory of empirical process techniques, whichhas so far been scattered in the statistical and probabilisticliterature, and surveys the most recent developments in variousrelated fields.Key features: A thorough and comprehensive introduction to theexisting theory of empirical process techniques for dependent data \*Accessible surveys by leading experts of the most recent developmentsin various related fields \* Examines empirical process techniques fordependent data, useful for studying parametric and non-parametricstatistical procedures \* Comprehensive bibliographies \* An overview ofapplications in various fields related to empirical processes: e.g.spectral analysis of time-series, the bootstrap for stationarysequences, extreme value theory, and the empirical process for mixingdependent observations, including the case of strong dependence.To date this book is the only comprehensive treatment of the topicin book literature. It is an ideal introductory text that will serveas a reference or resource for classroom use in the areas ofstatistics, time-series analysis, extreme value theory, point processtheory, and applied probability theory. Contributors: P. AngoNze, M.A. Arcones, I. Berkes, R. Dahlhaus, J. Dedecker, H.G. Dehling,Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 396 pp. Englisch. N° de réf. du vendeur 9781461266112
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Empirical Process Techniques for Dependent Data
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Birkhäuser Boston, Birkhäuser Boston, 2012
ISBN 10 : 1461266114
ISBN 13 : 9781461266112
Neuf
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Empirical process techniques for independent data have been used for many years in statistics and probability theory. These techniques have proved very useful for studying asymptotic properties of parametric as well as non-parametric statistical procedures. Recently, the need to model the dependence structure in data sets from many different subject areas such as finance, insurance, and telecommunications has led to new developments concerning the empirical distribution function and the empirical process for dependent, mostly stationary sequences. This work gives an introduction to this new theory of empirical process techniques, which has so far been scattered in the statistical and probabilistic literature, and surveys the most recent developments in various related fields. Key features: A thorough and comprehensive introduction to the existing theory of empirical process techniques for dependent data \* Accessible surveys by leading experts of the most recent developments in various related fields \* Examines empirical process techniques for dependent data, useful for studying parametric and non-parametric statistical procedures \* Comprehensive bibliographies \* An overview of applications in various fields related to empirical processes: e.g., spectral analysis of time-series, the bootstrap for stationary sequences, extreme value theory, and the empirical process for mixing dependent observations, including the case of strong dependence. To date this book is the only comprehensive treatment of the topic in book literature. It is an ideal introductory text that will serve as a reference or resource for classroom use in the areas of statistics, time-series analysis, extreme value theory, point process theory, and applied probability theory. Contributors: P. Ango Nze, M.A. Arcones, I. Berkes, R. Dahlhaus, J. Dedecker, H.G. Dehling, N° de réf. du vendeur 9781461266112
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Empirical Process Techniques for Dependent Data
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Birkhäuser, 2012
ISBN 10 : 1461266114
ISBN 13 : 9781461266112
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