This book offers an introduction to the field of stochastic analysis of Hermite processes. These selfsimilar stochastic processes with stationary increments liv

This book serves as a standard reference, making this area accessible not only to researchers in probability and statistics, but also to graduate students and p

The modeling of stochastic dependence is fundamental for understanding random systems evolving in time. When measured through linear correlation, many of these

Self-similar processes are stochastic processes that are invariant in distribution under suitable time scaling, and are a subject intensively studied in the las

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