The Bootstrap and Edgeworth Expansion - (Springer Statistics) by Peter Hall (Hardcover)
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<p/><br></br><p><b> About the Book </b></p></br></br>The aim of this book is to present a readable introduction to the theory of bootstrap methods which is suitable for graduate students and research workers in statistics. In particular, the author discusses the application of bootstrap methods to linear regression, non-parametric regression and density estimation.<p/><br></br><p><b> Book Synopsis </b></p></br></br>This monograph addresses two quite different topics, in the belief that each can shed light on the other. Firstly, it lays the foundation for a particular view of the bootstrap. Secondly, it gives an account of Edgeworth expansion. Chapter 1 is about the bootstrap, witih almost no mention of Edgeworth expansion; Chapter 2 is about Edgeworth expansion, with scarcely a word about the bootstrap; and Chapters 3 and 4 bring these two themes together, using Edgeworth expansion to explore and develop the properites of the bootstrap. The book is aimed a a graduate level audience who has some exposure to the methods of theoretical statistics. However, technical details are delayed until the last chapter (entitled "Details of Mathematical Rogour"), and so a mathematically able reader without knowledge of the rigorous theory of probability will have no trouble understanding the first four-fifths of the book. The book simultaneously fills two gaps in the literature; it provides a very readable graduate level account of the theory of Edgeworth expansion, and it gives a detailed introduction to the theory of bootstrap methods.<p/><br></br><p><b> Review Quotes </b></p></br></br><br>"...an up-to-date and comprehensive account of the title theme...provides a path to several major research frontiers in the bootstrap literature." - Journal of the American Statistical Association<br>
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