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230209s2011 xx o ||| 0 eng d |
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|a EBLCP
|b eng
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|d OCLCQ
|d OCLCO
|d EBLCP
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|d OCLCQ
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| 020 |
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|a 9781118625453
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|a 1118625455
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|a (OCoLC)1347026804
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|a 519.5/4
|q OCoLC
|2 22/eng/20231120
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| 049 |
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|a UAMI
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| 100 |
1 |
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|a Chernick, Michael R.
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| 245 |
1 |
3 |
|a An Introduction to Bootstrap Methods with Applications to R
|h [electronic resource].
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| 260 |
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|a Newark :
|b John Wiley & Sons, Incorporated,
|c 2011.
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| 300 |
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|a 1 online resource (236 p.).
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| 490 |
1 |
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|a New York Academy of Sciences Ser.
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| 500 |
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|a Description based upon print version of record.
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| 505 |
0 |
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|a Cover -- Title Page -- Copyright -- Contents -- Preface -- Acknowledgments -- List of Tables -- 1: INTRODUCTION -- 1.1 Historical Background -- 1.2 Definition and Relationship to the Delta Method and Other Resampling Methods -- 1.2.1 Jackknife -- 1.2.2 Delta Method -- 1.2.3 Cross Validation -- 1.2.4 Subsampling -- 1.3 Wide Range of Applications -- 1.4 The Bootstrap and the R Language System -- 1.5 Historical Notes -- 1.6 Exercises -- References -- 2: ESTIMATION -- 2.1 Estimating Bias -- 2.1.1 Bootstrap Adjustment -- 2.1.2 Error Rate Estimation in Discriminant Analysis
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| 505 |
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|a 2.1.3 Simple Example of Linear Discrimination and Bootstrap Error Rate Estimation -- 2.1.4 Patch Data Example -- 2.2 Estimating Location -- 2.2.1 Estimating a Mean -- 2.2.2 Estimating a Median -- 2.3 Estimating Dispersion -- 2.3.1 Estimating an Estimate's Standard Error -- 2.3.2 Estimating Interquartile Range -- 2.4 Linear Regression -- 2.4.1 Overview -- 2.4.2 Bootstrapping Residuals -- 2.4.3 Bootstrapping Pairs (response and Predictor Vector) -- 2.4.4 Heteroscedasticity of Variance: the Wild Bootstrap -- 2.4.5 a Special Class of Linear Regression Models: Multivariable Fractional Polynomials
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| 505 |
8 |
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|a 2.5 Nonlinear Regression -- 2.5.1 Examples of Nonlinear Models -- 2.5.2 a Quasi Optical Experiment -- 2.6 Nonparametric Regression -- 2.6.1 Examples of Nonparametric Regression Models -- 2.6.2 Bootstrap Bagging -- 2.7 Historical Notes -- 2.8 Exercises -- References -- 3: CONFIDENCE INTERVALS -- 3.1 Subsampling, Typical Value Theorem, and Efron's Percentile Method -- 3.2 Bootstrap-t -- 3.3 Iterated Bootstrap -- 3.4 Bias Corrected (BC) Bootstrap -- 3.5 Bca and Abc -- 3.6 Tilted Bootstrap -- 3.7 Variance Estimation with Small Sample Sizes -- 3.8 Historical Notes -- 3.9 Exercises -- References
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| 505 |
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|a 4: HYPOTHESIS TESTING -- 4.1 Relationship to Confidence Intervals -- 4.2 Why Test Hypotheses Differently? -- 4.3 Tendril Dx Example -- 4.4 Klingenberg Example: Binary Dose-response -- 4.5 Historical Notes -- 4.6 Exercises -- References -- 5: TIME SERIES -- 5.1 Forecasting Methods -- 5.2 Time Domain Models -- 5.3 Can Bootstrapping Improve Prediction Intervals? -- 5.4 Model Based Methods -- 5.4.1 Bootstrapping Stationary Autoregressive Processes -- 5.4.2 Bootstrapping Explosive Autoregressive Processes -- 5.4.3 Bootstrapping Unstable Autoregressive Processes
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| 505 |
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|a 5.4.4 Bootstrapping Stationary Arma Processes -- 5.5 Block Bootstrapping for Stationary Time Series -- 5.6 Dependent Wild Bootstrap (DWB) -- 5.7 Frequency-based Approaches for Stationary Time Series -- 5.8 Sieve Bootstrap -- 5.9 Historical Notes -- 5.10 Exercises -- References -- 6: BOOTSTRAP VARIANTS -- 6.1 Bayesian Bootstrap -- 6.2 Smoothed Bootstrap -- 6.3 Parametric Bootstrap -- 6.4 Double Bootstrap -- 6.5 the M-out-of-n Bootstrap -- 6.6 the Wild Bootstrap -- 6.7 Historical Notes -- 6.8 Exercise -- References -- 7: CHAPTER SPECIAL TOPICS -- 7.1 Spatial Data -- 7.1.1 Kriging
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| 500 |
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|a 7.1.2 Asymptotics for Spatial Data
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| 590 |
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|a ProQuest Ebook Central
|b Ebook Central Academic Complete
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| 655 |
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0 |
|a Electronic books.
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| 758 |
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|i has work:
|a An introduction to bootstrap methods with applications to R (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCFKtX6vcx9GDryw7JvkcHd
|4 https://id.oclc.org/worldcat/ontology/hasWork
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| 776 |
0 |
8 |
|i Print version:
|a Chernick, Michael R.
|t An Introduction to Bootstrap Methods with Applications to R
|d Newark : John Wiley & Sons, Incorporated,c2011
|z 9780470467046
|
| 830 |
|
0 |
|a New York Academy of Sciences Ser.
|
| 856 |
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|u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=7103888
|z Texto completo
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|b EBLB
|n EBL7103888
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