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Intended for class use or self-study, the second addition of this text aspires like the first to introduce statistical methodology to a wide audience, simply and intuitively, through resampling from the data at hand. The methodology proceeds from chapter to chapter from the simple to the complex.

Resampling (Statistics) --- Mathematics --- Probability --- Statistics

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Resampling (Statistics) --- Microsoft Excel (Computer file)

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This book gives a detailed account of bootstrap methods and their properties for dependent data, covering a wide range of topics such as block bootstrap methods, bootstrap methods in the frequency domain, resampling methods for long range dependent data, and resampling methods for spatial data. The first five chapters of the book treat the theory and applications of block bootstrap methods at the level of a graduate text. The rest of the book is written as a research monograph, with frequent references to the literature, but mostly at a level accessible to graduate students familiar with basic concepts in statistics. Supplemental background material is added in the discussion of such important issues as second order properties of bootstrap methods, bootstrap under long range dependence, and bootstrap for extremes and heavy tailed dependent data. Further, illustrative numerical examples are given all through the book and issues involving application of the methodology are discussed. The book fills a gap in the literature covering research on resampling methods for dependent data that has witnessed vigorous growth over the last two decades but remains scattered in various statistics and econometrics journals. It can be used as a graduate level text for a special topics course on resampling methods for dependent data and also as a research monograph for statisticians and econometricians who want to learn more about the topic and want to apply the methods in their own research. S.N. Lahiri is a professor of Statistics at the Iowa State University, is a Fellow of the Institute of Mathematical Statistics and a Fellow of the American Statistical Association.

Mathematical statistics --- Resampling (Statistics) --- 519.52 --- Resampling methods (Statistics) --- Nonparametric statistics --- Resampling (Statistics). --- Statistics . --- Statistical Theory and Methods. --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics

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Mathematical statistics --- Resampling (Statistics) --- Statistics --- Statistique mathématique --- Statistique mathématique.

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Econometrics. --- Economics, Mathematical --- Statistics --- Asymptotic efficiency. --- Data masking. --- Microaggregation. --- Nonparametric resampling.