9781461266112 - empirical process techniques for dependent data (12 resultados)
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Taschenbuch. Condición: 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 pr…ocedures. 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.
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Taschenbuch. Condición: 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-parametri…c 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.
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Condición: 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 a…s non-parametric statistical procedures.
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Condición: New. Print on Demand pp. 398 66:B&W 7 x 10 in or 254 x 178 mm Perfect Bound on White w/Gloss Lam.
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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Condición: New. PRINT ON DEMAND pp. 398.
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
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Taschenbuch. Condición: 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 stati…stical 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 Nature c/o IBS, Benzstrasse 21, 48619 Heek 396 pp. Englisch.
