Lecture Notes in Statistics: Properties and Examples

Doukhan, Paul

Mixing is concerned with the analysis of dependence between sigma-fields defined on the same underlying probability space. It provides an important tool of analysis for random fields, Markov processes, central limit theorems as well as being a topic of current research interest in its own right. The aim of this monograph is to provide a study of applications of dependence in probability and statistics. It is divided in two parts, the first covering the definitions and probabilistic properties of mixing theory. The second part describes mixing properties of classical processes and random fields as well as providing a detailed study of linear and Gaussian fields. Consequently, this book will provide statisticians dealing with problems involving weak dependence properties with a powerful tool.

Details

Published by: Springer

Publication Date: 1994-03-11

Format: Paperback

ISBN-13: 9780387942148

DOI: 10.1007/978-1-4612-2642-0

Dimensions: 235cm x155cm

Pages: 142