Stable Non-Gaussian Self-Similar Processes with Stationary Increments (Paperback, 1st ed. 2017)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	SpringerBriefs in Probability and Mathematical Statistics
Release date:	September 2017
First published:	2017
Authors:	Vladas Pipiras • Murad S Taqqu
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	135
Edition:	1st ed. 2017
ISBN-13:	978-3-319-62330-6
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Science & Mathematics > Mathematics > Applied mathematics > Non-linear science
LSN:	3-319-62330-3
Barcode:	9783319623306

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