05473nam 2200685 450 991046419690332120200520144314.01-118-62541-21-118-62545-5(CKB)3460000000120735(EBL)1771575(SSID)ssj0000719792(PQKBManifestationID)12297401(PQKBTitleCode)TC0000719792(PQKBWorkID)10660251(PQKB)10015253(MiAaPQ)EBC1771575(CaSebORM)9780470467046(Au-PeEL)EBL1771575(CaPaEBR)ebr10915823(CaONFJC)MIL639080(OCoLC)889674830(EXLCZ)99346000000012073520140902h20112011 uy 0engur|n|---|||||txtccrAn introduction to bootstrap methods with applications to R /Michael R. Chernick, Robert A. LaBudde1st editionHoboken, New Jersey :Wiley,2011.©20111 online resource (236 p.)Description based upon print version of record.1-322-07829-7 0-470-46704-5 Includes bibliographical references and index.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 Analysis2.1.3 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 Polynomials2.5 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 ; 4: HYPOTHESIS TESTING4.1 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 ; 5.4.4 Bootstrapping Stationary Arma Processes5.5 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 ; 7.1.2 Asymptotics for Spatial Data ; 7.1.3 Block Bootstrap on Regular Grids7.1.4 Block Bootstrap on Irregular GridsA comprehensive introduction to bootstrap methods in the R programming environment Bootstrap methods provide a powerful approach to statistical data analysis, as they have more general applications than standard parametric methods. An Introduction to Bootstrap Methods with Applications to R explores the practicality of this approach and successfully utilizes R to illustrate applications for the bootstrap and other resampling methods. This book provides a modern introduction to bootstrap methods for readers who do not have an extensive background in advanced mathematics. Emphasis throughout isBootstrap (Statistics)R (Computer program language)Electronic books.Bootstrap (Statistics)R (Computer program language)519.5/4Chernick Michael R.140081LaBudde Robert A.1947-MiAaPQMiAaPQMiAaPQBOOK9910464196903321An introduction to bootstrap methods with applications to R2015632UNINA01399nam0 22003011i 450 UON0052119120240109123824.5920231219d1995 |0itac50 baitaIT|||| |||||ˆI ‰figli di Glaukostemi e materiali di culture marinareGabriella Mondardini Morellicontributi di M. Carcangiu ... [et al.]SassariEdes1995158 p., [12] c. di tav.ill.21 cmDonazione prof.ssa Amalia SignorelliIT-UONSI F. Signorelli3 C685001UON005216902001 Quaderni del Laboratorio di antropologia cultura e socialeUniversità degli studi di Sassari, Dipartimento di economia, istituzioni e società1MARINAICulturaUONC102249FISassariUONL000427387.5092TRASPORTI MARITTIMI PERSONE22MONDARDINI MORELLIGabriellaUONV102426273624CarcangiuMUONV293756EDESUONV265662650ITSOL20240220RICASIBA - SISTEMA BIBLIOTECARIO DI ATENEOUONSIUON00521191SIBA - SISTEMA BIBLIOTECARIO DI ATENEOSI F. Signore3 C 685 SI 48602 5 Donazione prof.ssa Amalia SignorelliFigli di Glaukos3905705UNIOR