LEADER 03353nam 2200649Ia 450 001 9910451332203321 005 20200520144314.0 010 $a1-281-90585-2 010 $a9786611905859 010 $a981-270-349-7 035 $a(CKB)1000000000334370 035 $a(EBL)296160 035 $a(OCoLC)476063771 035 $a(SSID)ssj0000192601 035 $a(PQKBManifestationID)11171481 035 $a(PQKBTitleCode)TC0000192601 035 $a(PQKBWorkID)10187988 035 $a(PQKB)11457999 035 $a(MiAaPQ)EBC296160 035 $a(WSP)00001600 035 $a(Au-PeEL)EBL296160 035 $a(CaPaEBR)ebr10174127 035 $a(CaONFJC)MIL190585 035 $a(EXLCZ)991000000000334370 100 $a20060313d2005 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aLinear collider physics in the new millennium$b[electronic resource] /$feditors: Keisuke Fujii, David J. Miller, Amerjit Soni 210 $aHackensack, NJ $cWorld Scientific$dc2005 215 $a1 online resource (518 p.) 225 1 $aAdvanced series on directions in high energy physics ;$vvol. 19 300 $aDescription based upon print version of record. 311 $a981-238-908-3 320 $aIncludes bibliographical references and index. 327 $aPreface; Contents; List of Contributors; Chapter 1 The Machine and Detector G.A. Blair and D.J. Miller; Chapter 2 Higgs Physics at the Linear Collider John F. Gunion, Howard E. Haber and Rick Van Kooten; Chapter 3 Top Quark Physics Y. Sumino; Chapter 4 Supersymmetry and the Linear Collider Jonathan L . Feng and Mihoko M . Nojiri; Chapter 5 Dynamical Electroweak Symmetry Breaking Wolfgang Kilian; Chapter 6 Physics of Electroweak Gauge Bosons Klaus Monig; Chapter 7 New Physics at the TeV Scale and Beyond JoAnne L. Hewett; Chapter 8 QCD Philip N. Burrows 327 $aChapter 9 Gamma-Gamma and Other Options Tohru TakahashiChapter 10 CP Violation at the Linear Collider David Atwood and Amarjit Soni; Chapter 11 Overall Perspective Keisuke Fujai and Michael E. Peskin; Index 330 $aThe high energy electron-positron linear collider is expected to provide crucial clues to many of the fundamental questions of our time: What is the nature of electroweak symmetry breaking? Does a Standard Model Higgs boson exist, or does nature take the route of supersymmetry, technicolor or extra dimensions, or none of the foregoing? This invaluable book is a collection of articles written by experts on many of the most important topics which the linear collider will focus on. It is aimed primarily at graduate students but will undoubtedly be useful also to any active researcher on the physi 410 0$aAdvanced series on directions in high energy physics ;$vv. 19. 606 $aLinear colliders 606 $aSupersymmetry 608 $aElectronic books. 615 0$aLinear colliders. 615 0$aSupersymmetry. 676 $a539.757 701 $aFujii$b Keisuke$f1953-$0911548 701 $aMiller$b David J.$f1940-$0911549 701 $aSoni$b Amarjit$0911550 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910451332203321 996 $aLinear collider physics in the new millennium$92041270 997 $aUNINA LEADER 05473nam 2200685 450 001 9910464196903321 005 20200520144314.0 010 $a1-118-62541-2 010 $a1-118-62545-5 035 $a(CKB)3460000000120735 035 $a(EBL)1771575 035 $a(SSID)ssj0000719792 035 $a(PQKBManifestationID)12297401 035 $a(PQKBTitleCode)TC0000719792 035 $a(PQKBWorkID)10660251 035 $a(PQKB)10015253 035 $a(MiAaPQ)EBC1771575 035 $a(CaSebORM)9780470467046 035 $a(Au-PeEL)EBL1771575 035 $a(CaPaEBR)ebr10915823 035 $a(CaONFJC)MIL639080 035 $a(OCoLC)889674830 035 $a(EXLCZ)993460000000120735 100 $a20140902h20112011 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 13$aAn introduction to bootstrap methods with applications to R /$fMichael R. Chernick, Robert A. LaBudde 205 $a1st edition 210 1$aHoboken, New Jersey :$cWiley,$d2011. 210 4$dİ2011 215 $a1 online resource (236 p.) 300 $aDescription based upon print version of record. 311 $a1-322-07829-7 311 $a0-470-46704-5 320 $aIncludes bibliographical references and index. 327 $aCover ; 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 327 $a2.1.3 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 327 $a2.5 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 TESTING 327 $a4.1 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 Processes 327 $a5.5 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 Grids 327 $a7.1.4 Block Bootstrap on Irregular Grids 330 $aA 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 is 606 $aBootstrap (Statistics) 606 $aR (Computer program language) 608 $aElectronic books. 615 0$aBootstrap (Statistics) 615 0$aR (Computer program language) 676 $a519.5/4 700 $aChernick$b Michael R.$0140081 702 $aLaBudde$b Robert A.$f1947- 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910464196903321 996 $aAn introduction to bootstrap methods with applications to R$92015632 997 $aUNINA