01592cam a22002054a 4500008004100000020001800041020001500059040000800074050002500082100002500107245010700132260003500239300001900274505001700293518001500310520096900325650002701294650003401321700003101355110311s2011    njua     bs   001 0 eng    a9780470467046  a0470467045  aSDU00aQA276.8bC478 I 20111 aChernick, Michael R.13aAn introduction to bootstrap methods with applications to R /cMichael R. Chernick, Robert A. LaBudde.  aHoboken, N.J. :bWiley,c2011.  a216 p. :bill.  aHKBU library  aYT2025 M08  a"This book provides both an elementary and a modern introduction to the bootstrap for students who do not have an extensive background in advanced mathematics. It offers reliable, hands-on coverage of the bootstrap's considerable advantages -- as well as its drawbacks. The book outpaces the competition by skillfully presenting results on improved confidence set estimation, estimation of error rates in discriminant analysis, and applications to a wide variety of hypothesis testing and estimation problems. To alert readers to the limitations of the method, the book exhibits counterexamples to the consistency of bootstrap methods. The authors take great care to draw connections between the more traditional resampling methods and the bootstrap, oftentimes displaying helpful computer routines in R. Emphasis throughout the book is on the use of the bootstrap as an exploratory tool including its value in variable selection and other modeling environments"-- 0aBootstrap (Statistics) 0aR (Computer program language)1 aLaBudde, Robert A.,d1947-