Introduction to statistical limit theory
By: Alan M. Polansky
Series: Chapman & Hall/CRC texts in statistical science series; Texts in statistical science
Publisher: Chapman & Hall/CRC Press
Published: 2011
Place of publication: Boca Raton, FL
Language: eng
Number of pages: 625
ISBN-13: 9781420076608
Subjects: Limit theorems (Probability theory)
Description: "Helping students develop a good understanding of asymptotic theory, Introduction to Statistical Limit Theory provides a thorough yet accessible treatment of common modes of convergence and their related tools used in statistics. It also discusses how the results can be applied to several common areas in the field.The author explains as much of the background material as possible and offers a comprehensive account of the modes of convergence of random variables, distributions, and moments, establishing a firm foundation for the applications that appear later in the book. The text includes detailed proofs that follow a logical progression of the central inferences of each result. It also presents in-depth explanations of the results and identifies important tools and techniques. Through numerous illustrative examples, the book shows how asymptotic theory offers deep insight into statistical problems, such as confidence intervals, hypothesis tests, and estimation. With an array of exercises and experiments in each chapter, this classroom-tested book gives students the mathematical foundation needed to understand asymptotic theory. It covers the necessary introductory material as well as modern statistical applications, exploring how the underlying mathematical and statistical theories work together"--Provided by publisher.

"Those moving on to advanced statistics typically lack the mathematical foundation that allows them to make full use of statistical limit theory. This accessible resource reviews approximation theory and limit theory for sequences of functions and basic notions of functional analysis. It provides detailed arguments that show how underlying mathematical and statistical theory work together. Among its unique qualities, the text covers expansion theory, which is becoming increasingly important in modern applications. It also discusses bootstrap, kernel smoothing, and Markov chain Monte Carlo and includes a wide array of examples and problems from the fundamental to very advanced"--Provided by publisher.
Notes: Includes bibliographical references and index.