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Springer Weak Convergence and Empirical Processes Book

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Description

Explore the fundamentals of stochastic convergence and empirical processes with this comprehensive text from Springer. Part of the Springer Series in Statistics, this book provides a thorough treatment of weak convergence theory and its practical applications in statistical problems. The text is organized into three distinct parts to assist both statisticians and probabilists. The first section covers various forms of stochastic convergence, while the second part presents empirical process theory in an accessible format. The final section applies these concepts to essential statistical areas, including the bootstrap, semiparametric estimation, and the functional delta-method. This volume is an essential resource for understanding limit theorems for M- and Z-estimators and the rates of convergence for estimators.

Key Features

This Springer Series in Statistics volume provides a thorough account of weak convergence theory and empirical processes.

The book covers stochastic convergence in its various forms within the first part of the text.

Part 2 offers an accessible presentation of empirical process theory for both statisticians and probabilists.

Statistical applications included are the bootstrap, semiparametric estimation, and the functional delta-method.

The text details important concepts such as limit theorems for M- and Z-estimators and rates of convergence of estimators.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
12 July 2023
Listed Since
12 July 2023

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