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Weak Convergence and Empirical Processes: With Applications to Statistics (Springer Series in Statistics) - Hardcover
Synopsis
This book explores weak convergence theory and empirical processes and their applications to many applications in statistics. Part one reviews stochastic convergence in its various forms. Part two offers the theory of empirical processes in a form accessible to statisticians and probabilists. Part three covers a range of topics demonstrating the applicability of the theory to key questions such as measures of goodness of fit and the bootstrap.
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Review
"...succeeds and complements Billingsleys classic work and will become the standard source of study and reference for students and researchers...." The Statistician
Synopsis
This book provides an account of weak convergence theory and empirical processes and their applications to a wide variety of applications in statistics. The first part of the book presents a thorough account of stocastic convergence in its various forms. Part 2 brings together the theory of empirical processes in a form accessible to statisticians and probabilists. In Part 3, the authors cover a range of topics which demonstrate the applicability of the theory to important questions such as: limit theorems in asymptotic statistics; measures of goodness of fit; the bootstrap; and semiparametric estimation. Most of the sections conclude with "problems and complements." Some of these are exercises to help the reader's understanding of the material whereas others are intended to supplement the text.
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Weak Convergence and Empirical Processes. With Applications to Statistics
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Weak Convergence and Empirical Processes: With Applications to Statistics (Springer Series in Statistics)
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Weak Convergence and Empirical Processes: With Applications to Statistics (Springer Series in Statistics)
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