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

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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.

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Product Description

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.

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Product Details

General

Imprint

Springer International Publishing AG

Country of origin

Switzerland

Series

SpringerBriefs in Probability and Mathematical Statistics

Release date

September 2017

Availability

Expected to ship within 10 - 15 working days

First published

2017

Authors

,

Dimensions

235 x 155mm (L x W)

Format

Paperback

Pages

135

Edition

1st ed. 2017

ISBN-13

978-3-319-62330-6

Barcode

9783319623306

Categories

LSN

3-319-62330-3



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