LEADER 05233nam 22007094a 450 001 9910828285803321 005 20200520144314.0 010 $a1-281-21679-8 010 $a9786611216795 010 $a0-387-74978-0 024 7 $a10.1007/978-0-387-74978-5 035 $a(CKB)1000000000403660 035 $a(EBL)337320 035 $a(OCoLC)233972325 035 $a(SSID)ssj0000182548 035 $a(PQKBManifestationID)11172434 035 $a(PQKBTitleCode)TC0000182548 035 $a(PQKBWorkID)10171998 035 $a(PQKB)10224080 035 $a(DE-He213)978-0-387-74978-5 035 $a(MiAaPQ)EBC337320 035 $a(Au-PeEL)EBL337320 035 $a(CaPaEBR)ebr10223041 035 $a(CaONFJC)MIL121679 035 $a(PPN)123737311 035 $a(EXLCZ)991000000000403660 100 $a20071107d2008 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aIntroduction to empirical processes and semiparametric inference$b[electronic resource] /$fMichael R. Kosorok 205 $a1st ed. 2008. 210 $aNew York $cSpringer$dc2008 215 $a1 online resource (495 p.) 225 1 $aSpringer Series in Statistics,$x0172-7397 300 $aDescription based upon print version of record. 311 $a0-387-74977-2 320 $aIncludes bibliographical references (p. [459]-469) and indexes. 327 $aOverview -- An Overview of Empirical Processes -- Overview of Semiparametric Inference -- Case Studies I -- Empirical Processes -- to Empirical Processes -- Preliminaries 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 -- Semiparametric Inference -- to Semiparametric Inference -- Preliminaries for Semiparametric Inference -- Semiparametric Models and Efficiency -- Efficient Inference for Finite-Dimensional Parameters -- Efficient Inference for Infinite-Dimensional Parameters -- Semiparametric M-Estimation -- Case Studies III. 330 $aThis 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 inference 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 probability. The book consists of three parts. The first part is a concise overview of all of the main concepts covered in the book with a minimum of technicalities. The second and third parts cover the two respective main topics of empirical processes and semiparametric inference in depth. The connections between these two topics is also demonstrated and emphasized throughout the text. Each part has a final chapter with several case studies that use concrete examples to illustrate the concepts developed so far. The last two parts also each include a chapter which covers the needed mathematical preliminaries. Each main idea is introduced with a non-technical motivation, and examples are given throughout to illustrate important concepts. Homework problems are also included at the end of each chapter to help the reader gain additional insights. Michael R. Kosorok is Professor and Chair, Department of Biostatistics, and Professor, Department of Statistics and Operations Research, at the University of North Carolina at Chapel Hill. His research has focused on the application of empirical processes and semiparametric inference to statistics and biostatistics. He is a Fellow of both the American Statistical Association and the Institute of Mathematical Statistics. He is an Associate Editor of the Annals of Statistics, Electronic Journal of Statistics, International Journal of Biostatistics, Statistics and Probability Letters, and Statistics Surveys. 410 0$aSpringer Series in Statistics,$x0172-7397 606 $aStochastic processes 606 $aSampling (Statistics) 606 $aProbabilities 606 $aEstimation theory 606 $aConvergence 615 0$aStochastic processes. 615 0$aSampling (Statistics) 615 0$aProbabilities. 615 0$aEstimation theory. 615 0$aConvergence. 676 $a519.2/3 700 $aKosorok$b Michael R$0614537 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910828285803321 996 $aIntroduction to empirical processes and semiparametric inference$91131119 997 $aUNINA