This book provides a self-contained presentation on the structure of a
large class of stable processes, known as self-similar mixed moving
averages. The authors present a way to describe and classify these
processes by relating them to so-called deterministic flows. The first
sections in the book review random variables, stochastic processes, and
integrals, moving on to rigidity and flows, and finally ending with
mixed moving averages and self-similarity. In-depth appendices are also
included.
This book is aimed at graduate students and researchers working in
probability theory and statistics.