Articles liés à Resampling Methods for Dependent Data
Synopsis
By giving a detailed account of bootstrap methods and their properties for dependent data, this book provides illustrative numerical examples throughout. The book fills a gap in the literature covering research on re-sampling methods for dependent data that has witnessed vigorous growth over the last two decades but remains scattered in various statistics and econometrics journals. It can be used as a graduate level text and also as a research monograph for statisticians and econometricians.
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- ÉditeurSpringer-Verlag New York Inc.
- Date d'édition2003
- ISBN 10 0387009280
- ISBN 13 9780387009285
- ReliureRelié
- Langueanglais
- Nombre de pages374
- Coordonnées du fabricantnon disponible
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Resampling Methods for Dependent Data
Edité par
Springer New York, 2003
ISBN 10 : 0387009280
ISBN 13 : 9780387009285
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Vendeur : Better World Books, Mishawaka, IN, Etats-Unis
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Resampling Methods for Dependent Data (Springer Series in Statistics)
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hardcover. Etat : New. In shrink wrap. Looks like an interesting title! N° de réf. du vendeur Q-0387009280
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Resampling Methods for Dependent Data (Springer Series in Statistics)
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Resampling Methods for Dependent Data
Edité par
Springer New York, 2003
ISBN 10 : 0387009280
ISBN 13 : 9780387009285
Neuf
Couverture rigide
Vendeur : moluna, Greven, Allemagne
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Gebunden. Etat : New. By giving a detailed account of bootstrap methods and their properties for dependent data, this book provides illustrative numerical examples throughout. The book fills a gap in the literature covering research on re-sampling methods for dependent data t. N° de réf. du vendeur 5908862
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Resampling Methods for Dependent Data
Edité par
Springer New York, Springer US Aug 2003, 2003
ISBN 10 : 0387009280
ISBN 13 : 9780387009285
Neuf
Couverture rigide
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This is a book on bootstrap and related resampling methods for temporal and spatial data exhibiting various forms of dependence. Like the resam pling methods for independent data, these methods provide tools for sta tistical analysis of dependent data without requiring stringent structural assumptions. This is an important aspect of the resampling methods in the dependent case, as the problem of model misspecification is more preva lent under dependence and traditional statistical methods are often very sensitive to deviations from model assumptions. Following the tremendous success of Efron's (1979) bootstrap to provide answers to many complex problems involving independent data and following Singh's (1981) example on the inadequacy of the method under dependence, there have been several attempts in the literature to extend the bootstrap method to the dependent case. A breakthrough was achieved when resampling of single observations was replaced with block resampling, an idea that was put forward by Hall (1985), Carlstein (1986), Kiinsch (1989), Liu and Singh (1992), and others in various forms and in different inference problems. There has been a vig orous development in the area of res amp ling methods for dependent data since then and it is still an area of active research. This book describes various aspects of the theory and methodology of resampling methods for dependent data developed over the last two decades. There are mainly two target audiences for the book, with the level of exposition of the relevant parts tailored to each audience. 396 pp. Englisch. N° de réf. du vendeur 9780387009285
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Resampling Methods for Dependent Data
Edité par
Springer New York, Springer US Aug 2003, 2003
ISBN 10 : 0387009280
ISBN 13 : 9780387009285
Neuf
Couverture rigide
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. Neuware -This is a book on bootstrap and related resampling methods for temporal and spatial data exhibiting various forms of dependence. Like the resam pling methods for independent data, these methods provide tools for sta tistical analysis of dependent data without requiring stringent structural assumptions. This is an important aspect of the resampling methods in the dependent case, as the problem of model misspecification is more preva lent under dependence and traditional statistical methods are often very sensitive to deviations from model assumptions. Following the tremendous success of Efron's (1979) bootstrap to provide answers to many complex problems involving independent data and following Singh's (1981) example on the inadequacy of the method under dependence, there have been several attempts in the literature to extend the bootstrap method to the dependent case. A breakthrough was achieved when resampling of single observations was replaced with block resampling, an idea that was put forward by Hall (1985), Carlstein (1986), Kiinsch (1989), Liu and Singh (1992), and others in various forms and in different inference problems. There has been a vig orous development in the area of res amp ling methods for dependent data since then and it is still an area of active research. This book describes various aspects of the theory and methodology of resampling methods for dependent data developed over the last two decades. There are mainly two target audiences for the book, with the level of exposition of the relevant parts tailored to each audience.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 396 pp. Englisch. N° de réf. du vendeur 9780387009285
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Resampling Methods for Dependent Data
Edité par
Springer New York, Springer US, 2003
ISBN 10 : 0387009280
ISBN 13 : 9780387009285
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This is a book on bootstrap and related resampling methods for temporal and spatial data exhibiting various forms of dependence. Like the resam pling methods for independent data, these methods provide tools for sta tistical analysis of dependent data without requiring stringent structural assumptions. This is an important aspect of the resampling methods in the dependent case, as the problem of model misspecification is more preva lent under dependence and traditional statistical methods are often very sensitive to deviations from model assumptions. Following the tremendous success of Efron's (1979) bootstrap to provide answers to many complex problems involving independent data and following Singh's (1981) example on the inadequacy of the method under dependence, there have been several attempts in the literature to extend the bootstrap method to the dependent case. A breakthrough was achieved when resampling of single observations was replaced with block resampling, an idea that was put forward by Hall (1985), Carlstein (1986), Kiinsch (1989), Liu and Singh (1992), and others in various forms and in different inference problems. There has been a vig orous development in the area of res amp ling methods for dependent data since then and it is still an area of active research. This book describes various aspects of the theory and methodology of resampling methods for dependent data developed over the last two decades. There are mainly two target audiences for the book, with the level of exposition of the relevant parts tailored to each audience. N° de réf. du vendeur 9780387009285
Quantité disponible : 1 disponible(s)
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Resampling Methods for Dependent Data (Springer Series in Statistics)
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
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Resampling Methods for Dependent Data
Vendeur : Books Puddle, New York, NY, Etats-Unis
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Etat : New. pp. 396. N° de réf. du vendeur 26315748
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Resampling Methodes for Dependant Data (Springer Series in Statistics)
Vendeur : Revaluation Books, Exeter, Royaume-Uni
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Hardcover. Etat : Brand New. 1st edition. 324 pages. 9.25x6.25x0.75 inches. In Stock. N° de réf. du vendeur x-0387009280
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