Mixing: Properties and Examples (Lecture Notes in Statistics)

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 and 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 into two parts, the first covering the definitions and probabilistic properties of mixing theory, the second describing mixing properties of classical processes and random fields as well as providing a detailed study of linear and Gaussian fields.