Stable Non-Gaussian Self-Similar Processes with Stationary Increments by Vladas

Description: Stable Non-Gaussian Self-Similar Processes with Stationary Increments by Vladas Pipiras, Murad S. Taqqu 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 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. FORMAT Paperback LANGUAGE English CONDITION Brand New Publisher 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. Author Biography Vladas Pipiras is Professor of Statistics and Operations Research at the University of North Carolina, Chapel Hill. His main research interests focus on stochastic processes exhibiting long-range dependence, self-similarity and other scaling phenomena, as well as on stable, extreme-value and other distributions possessing heavy tails. His other current interests include high-dimensional time series, sampling issues for "big data" and stochastic dynamical systems, with applications in Econometrics, Neuroscience, Engineering, Computer Science and other areas. Vladas Pipiras has written over 50 research papers, and is a coauthor of a graduate textbook on measure theory and probability.Murad S. Taqqus research involves self-similar processes, their connection to time series with long-range dependence , the development of statistical tests, and the study of non-Gaussian processes whose marginal distributions have heavy tails. He has written more than 250 scientificpapers and is the coauthor of a standard reference on stable non-Gaussian random processes. Professor Taqqu is a Fellow of the Institute of Mathematical Statistics and has been elected Member of the International Statistical Institute. He has received a number of awards, including a John Simon Guggenheim Fellowship, the 1995 William J. Bennett Award, the 1996 IEEE W.R.G. Baker Prize, the 2002 EURASIO Best Paper Award and the 2006 ACM/SIGCOMM Test of Time Award. Table of Contents Preliminaries.- Minimality, Rigidity, and Flows.- Mixed Moving Averages and Self-similarity.- A. Historical Notes.- B. Standard Lebesgue Spaces and Projections.- C. Notation Summary. Feature The first book providing a self-contained account of the subject Contains numerous examples that facilitate and enhance reading Brings together probability theory and ergodic theory Details ISBN3319623303 Author Murad S. Taqqu Year 2017 ISBN-10 3319623303 ISBN-13 9783319623306 Format Paperback Edition 1st Imprint Springer International Publishing AG Place of Publication Cham Country of Publication Switzerland DEWEY 515.39 Illustrations 2 Illustrations, black and white; XIII, 135 p. 2 illus. Pages 135 Language English Media Book Publication Date 2017-09-08 Edited by Konstantin Vorontsov Birth 1945 Affiliation Sorbonne Nouvelle University, France Position Contributor Qualifications M.D Publisher Springer International Publishing AG Edition Description 1st ed. 2017 Series SpringerBriefs in Probability and Mathematical Statistics Audience Professional & Vocational We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:117367089;

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