Bootstrap methods and their application
Bootstrap methods are computer-intensive methods of statistical analysis, which use simulation to calculate standard errors, confidence intervals, and significance tests. The methods apply for any level of modelling, and so can be used for fully parametric, semiparametric, and completely nonparametr...
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| Sprache: | English |
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Cambridge
Cambridge University Press
1997
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| Schriftenreihe: | Cambridge series on statistical and probabilistic mathematics
1 |
| Online-Zugang: | Volltext |
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| 100 | 1 | |a Davison, A. C. | |
| 245 | 1 | 0 | |a Bootstrap methods and their application |c A.C. Davison, D.V. Hinkley |
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| 520 | |a Bootstrap methods are computer-intensive methods of statistical analysis, which use simulation to calculate standard errors, confidence intervals, and significance tests. The methods apply for any level of modelling, and so can be used for fully parametric, semiparametric, and completely nonparametric analysis. This 1997 book gives a broad and up-to-date coverage of bootstrap methods, with numerous applied examples, developed in a coherent way with the necessary theoretical basis. Applications include stratified data; finite populations; censored and missing data; linear, nonlinear, and smooth regression models; classification; time series and spatial problems. Special features of the book include: extensive discussion of significance tests and confidence intervals; material on various diagnostic methods; and methods for efficient computation, including improved Monte Carlo simulation. Each chapter includes both practical and theoretical exercises. S-Plus programs for implementing the methods described in the text are available from the supporting website. | ||
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| spelling | Davison, A. C. Bootstrap methods and their application A.C. Davison, D.V. Hinkley Bootstrap Methods & their Application Cambridge Cambridge University Press 1997 1 Online-Ressource (x, 582 Seiten) txt c cr Cambridge series on statistical and probabilistic mathematics 1 Bootstrap methods are computer-intensive methods of statistical analysis, which use simulation to calculate standard errors, confidence intervals, and significance tests. The methods apply for any level of modelling, and so can be used for fully parametric, semiparametric, and completely nonparametric analysis. This 1997 book gives a broad and up-to-date coverage of bootstrap methods, with numerous applied examples, developed in a coherent way with the necessary theoretical basis. Applications include stratified data; finite populations; censored and missing data; linear, nonlinear, and smooth regression models; classification; time series and spatial problems. Special features of the book include: extensive discussion of significance tests and confidence intervals; material on various diagnostic methods; and methods for efficient computation, including improved Monte Carlo simulation. Each chapter includes both practical and theoretical exercises. S-Plus programs for implementing the methods described in the text are available from the supporting website. Hinkley, D. V. Erscheint auch als Druck-Ausgabe 9780521573917 Erscheint auch als Druck-Ausgabe 9780521574716 TUM01 ZDB-20-CTM TUM_PDA_CTM https://doi.org/10.1017/CBO9780511802843 Volltext |
| spellingShingle | Davison, A. C. Bootstrap methods and their application |
| title | Bootstrap methods and their application |
| title_alt | Bootstrap Methods & their Application |
| title_auth | Bootstrap methods and their application |
| title_exact_search | Bootstrap methods and their application |
| title_full | Bootstrap methods and their application A.C. Davison, D.V. Hinkley |
| title_fullStr | Bootstrap methods and their application A.C. Davison, D.V. Hinkley |
| title_full_unstemmed | Bootstrap methods and their application A.C. Davison, D.V. Hinkley |
| title_short | Bootstrap methods and their application |
| title_sort | bootstrap methods and their application |
| url | https://doi.org/10.1017/CBO9780511802843 |
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