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Introduction to empirical processes and semiparametric inference /
"This book provides a self-contained, linear, and unified introduction to empirical processes and semiparametric inference. These powerful research techniques are surprisingly useful for developing methods of statistical reference for complex models and in understanding the properties of such m...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York, N.Y. :
Springer,
©2008.
|
| Colección: | Springer series in statistics.
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Kosorok, Michael R. | |
| 245 | 1 | 0 | |a Introduction to empirical processes and semiparametric inference / |c Michael R. Kosorok. |
| 246 | 3 | 0 | |a Empirical processes and semiparametric inference |
| 246 | 3 | 0 | |a Semiparametric inference |
| 260 | |a New York, N.Y. : |b Springer, |c ©2008. | ||
| 300 | |a 1 online resource (xiv, 483 pages) | ||
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| 490 | 1 | |a Springer series in statistics | |
| 504 | |a Includes bibliographical references (pages 459-469)-and indexes. | ||
| 520 | 1 | |a "This book provides a self-contained, linear, and unified introduction to empirical processes and semiparametric inference. These powerful research techniques are surprisingly useful for developing methods of statistical reference for complex models and in understanding the properties of such methods. The targeted audience includes statisticians, biostatisticians, and other researchers with a background in mathematical statistics who have an interest in learning about and doing research in empirical processes and semiparametric inference but who would like to have a friendly and gradual introduction to the area. The book can be used either as a research reference or as a textbook. The level of the book is suitable for a second year graduate course in statistics or biostatistics, provided the students have had a year of graduate level mathematical statistics and a semester of provability."--Jacket. | |
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Introduction -- An Overview of The Empirical Processes -- Overview of Semiparametric Inference -- Case Studies I -- Introduction to Empirical Processes -- Preliminiaries for Empirical Processes -- Stochastic Convergence -- Empirical Process Methods -- Entropy Calculations -- Bootstrapping Empirical Processes -- Additional Empirical Process Results -- The Functional Delta Method -- Z-Estimators -- M-Estimators -- Case Studies II -- Introduction To Semiparametric Inference -- Seimparametric Models and Efficiency -- Efficient Inference for Fininte-Dimensional Parameters -- Efficient Inference for Infinite-Dimensional Parameters -- Semiparametric M-Estimators -- Case Studies III. | |
| 506 | |3 Use copy |f Restrictions unspecified |2 star |5 MiAaHDL | ||
| 533 | |a Electronic reproduction. |b [Place of publication not identified] : |c HathiTrust Digital Library, |d 2011. |5 MiAaHDL | ||
| 538 | |a Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. |u http://purl.oclc.org/DLF/benchrepro0212 |5 MiAaHDL | ||
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| 650 | 0 | |a Empiricism |x Mathematical models |v Case studies. | |
| 650 | 0 | |a Parameter estimation |x Mathematical models |v Case studies. | |
| 650 | 0 | |a Estimation theory |x Mathematical models |v Case studies. | |
| 650 | 0 | |a Stochastic systems |x Mathematical models |v Case studies. | |
| 650 | 2 | |a Models, Statistical | |
| 650 | 6 | |a Empirisme |x Modèles mathématiques |v Études de cas. | |
| 650 | 6 | |a Estimation d'un paramètre |x Modèles mathématiques |v Études de cas. | |
| 650 | 6 | |a Théorie de l'estimation |x Modèles mathématiques |v Études de cas. | |
| 650 | 6 | |a Systèmes stochastiques |x Modèles mathématiques |v Études de cas. | |
| 650 | 7 | |a PHILOSOPHY |x Movements |x Empiricism. |2 bisacsh | |
| 650 | 7 | |a MATHEMATICS |x Probability & Statistics |x Stochastic Processes. |2 bisacsh | |
| 650 | 0 | 7 | |a Parameter estimation |x Mathematical models. |2 cct |
| 650 | 0 | 7 | |a Estimation theory |x Mathematical models. |2 cct |
| 650 | 0 | 7 | |a Stochastic systems |x Mathematical models. |2 cct |
| 650 | 0 | 7 | |a Empiricism |x Mathematical models. |2 cct |
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| 650 | 7 | |a Empirismo |2 embne | |
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| 650 | 7 | |a Parameter estimation |x Mathematical models |2 fast | |
| 650 | 7 | |a Stochastic systems |x Mathematical models |2 fast | |
| 650 | 7 | |a Empirischer Prozess |2 gnd | |
| 650 | 7 | |a Semiparametrisches Verfahren |2 gnd | |
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| 776 | 0 | 8 | |i Print version: |a Kosorok, Michael R. |t Introduction to empirical processes and semiparametric inference. |d New York, N.Y., USA : Springer, ©2008 |z 0387749772 |z 9780387749778 |w (DLC) 2007940955 |w (OCoLC)213356750 |
| 830 | 0 | |a Springer series in statistics. | |
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