Asymptotic Stochastics : An Introduction with a View towards Statistics / by Norbert Henze.

Format:

Book

Author/Creator:

Henze, Norbert, 1951- author.

Series:

Mathematics Study Resources, 2731-3832 ; 10

Language:

English

Subjects (All):

Probabilities.

Statistics.

Probability Theory.

Local Subjects:

Probability Theory.

Statistics.

Physical Description:

1 online resource (XIX, 467 p.)

Edition:

1st ed. 2024.

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2024.

Summary:

This textbook, which is based on the second edition of a book that has been previously published in German language, provides a comprehension-oriented introduction to asymptotic stochastics. It is aimed at the beginning of a master's degree course in mathematics and covers the material that can be taught in a four-hour lecture with two-hour exercises. Individual chapters are also suitable for seminars at the end of a bachelor's degree course. In addition to more basic topics such as the method of moments in connection with the convergence in distribution or the multivariate central limit theorem and the delta method, the book covers limit theorems for U-statistics, the Wiener process and Donsker's theorem, as well as the Brownian bridge, with applications to statistics. It concludes with a central limit theorem for triangular arrays of Hilbert space-valued random elements with applications to weighted L² statistics. The book is deliberately designed for self-study. It contains 138 self-questions, which are answered at the end of each chapter, as well as 194 exercises with solutions. The Author Norbert Henze is a retired professor of stochastics at the Karlsruhe Institute of Technology (KIT). He was awarded the Ars legendi Faculty Prize 2014 for excellent university teaching in mathematics. This book is a translation of an original German edition. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation.

Contents:

Preface

List of Symbols

1 Prerequisites from Probability Theory

2 A Poisson Limit Theorem for Triangular Arrays

3 The Method of Moments

4 A Central Limit Theorem for Stationary m-Dependent Sequences

5 The multivariate normal distribution

6 Convergence in Distribution and Central Limit Theorem in Rd

7 Empirical Distribution Function

8 Limit Theorems for U-Statistics

9 Basic Concepts of Estimation Theory

10 Maximum Likelihood Estimation

11 Asymptotic (relative) efficiency of estimators

12 Likelihood Ratio Tests

13 Probability Measures on Metric Spaces

14 Convergence of Distributions in Metric Spaces

15 Wiener Process, Donsker’s Theorem, and Brownian Bridge

16 The Space D[0,1], Empirical Processes

17 Random Elements in Separable Hilbert Spaces

Afterword

Solutions to the Problems

Bibliography

Index.

Notes:

Includes bibliographical references and index.

ISBN:

9783662689233

3662689235