Non-Gaussian Selfsimilar Stochastic Processes

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Publisher :
ISBN 13 : 9783031337734
Total Pages : 0 pages
Book Rating : 4.35/5 ( download)

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Book Synopsis Non-Gaussian Selfsimilar Stochastic Processes by : Ciprian Tudor

Download or read book Non-Gaussian Selfsimilar Stochastic Processes written by Ciprian Tudor and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers an introduction to the field of stochastic analysis of Hermite processes. These selfsimilar stochastic processes with stationary increments live in a Wiener chaos and include the fractional Brownian motion, the only Gaussian process in this class. Using the Wiener chaos theory and multiple stochastic integrals, the book covers the main properties of Hermite processes and their multiparameter counterparts, the Hermite sheets. It delves into the probability distribution of these stochastic processes and their sample paths, while also presenting the basics of stochastic integration theory with respect to Hermite processes and sheets. The book goes beyond theory and provides a thorough analysis of physical models driven by Hermite noise, including the Hermite Ornstein-Uhlenbeck process and the solution to the stochastic heat equation driven by such a random perturbation. Moreover, it explores up-to-date topics central to current research in statistical inference for Hermite-driven models.

Stable Non-Gaussian Self-Similar Processes with Stationary Increments

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Publisher : Springer
ISBN 13 : 3319623311
Total Pages : 143 pages
Book Rating : 4.13/5 ( download)

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Book Synopsis Stable Non-Gaussian Self-Similar Processes with Stationary Increments by : Vladas Pipiras

Download or read book Stable Non-Gaussian Self-Similar Processes with Stationary Increments written by Vladas Pipiras and published by Springer. This book was released on 2017-08-31 with total page 143 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Non-Gaussian Selfsimilar Stochastic Processes

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Publisher : Springer Nature
ISBN 13 : 3031337727
Total Pages : 110 pages
Book Rating : 4.27/5 ( download)

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Book Synopsis Non-Gaussian Selfsimilar Stochastic Processes by : Ciprian Tudor

Download or read book Non-Gaussian Selfsimilar Stochastic Processes written by Ciprian Tudor and published by Springer Nature. This book was released on 2023-07-04 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers an introduction to the field of stochastic analysis of Hermite processes. These selfsimilar stochastic processes with stationary increments live in a Wiener chaos and include the fractional Brownian motion, the only Gaussian process in this class. Using the Wiener chaos theory and multiple stochastic integrals, the book covers the main properties of Hermite processes and their multiparameter counterparts, the Hermite sheets. It delves into the probability distribution of these stochastic processes and their sample paths, while also presenting the basics of stochastic integration theory with respect to Hermite processes and sheets. The book goes beyond theory and provides a thorough analysis of physical models driven by Hermite noise, including the Hermite Ornstein-Uhlenbeck process and the solution to the stochastic heat equation driven by such a random perturbation. Moreover, it explores up-to-date topics central to current research in statistical inference for Hermite-driven models.

Stable Non-Gaussian Random Processes

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Publisher : Routledge
ISBN 13 : 1351414798
Total Pages : 519 pages
Book Rating : 4.91/5 ( download)

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Book Synopsis Stable Non-Gaussian Random Processes by : Gennady Samoradnitsky

Download or read book Stable Non-Gaussian Random Processes written by Gennady Samoradnitsky and published by Routledge. This book was released on 2017-11-22 with total page 519 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 practitioners. The book assumes only a first-year graduate course in probability. Each chapter begins with a brief overview and concludes with a wide range of exercises at varying levels of difficulty. The authors supply detailed hints for the more challenging problems, and cover many advances made in recent years.

Analysis of Variations for Self-similar Processes

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Publisher : Springer Science & Business Media
ISBN 13 : 3319009362
Total Pages : 272 pages
Book Rating : 4.60/5 ( download)

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Book Synopsis Analysis of Variations for Self-similar Processes by : Ciprian Tudor

Download or read book Analysis of Variations for Self-similar Processes written by Ciprian Tudor and published by Springer Science & Business Media. This book was released on 2013-08-13 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Self-similar processes are stochastic processes that are invariant in distribution under suitable time scaling, and are a subject intensively studied in the last few decades. This book presents the basic properties of these processes and focuses on the study of their variation using stochastic analysis. While self-similar processes, and especially fractional Brownian motion, have been discussed in several books, some new classes have recently emerged in the scientific literature. Some of them are extensions of fractional Brownian motion (bifractional Brownian motion, subtractional Brownian motion, Hermite processes), while others are solutions to the partial differential equations driven by fractional noises. In this monograph the author discusses the basic properties of these new classes of self-similar processes and their interrelationship. At the same time a new approach (based on stochastic calculus, especially Malliavin calculus) to studying the behavior of the variations of self-similar processes has been developed over the last decade. This work surveys these recent techniques and findings on limit theorems and Malliavin calculus.

Selfsimilar Processes

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Publisher : Princeton University Press
ISBN 13 : 1400825105
Total Pages : 128 pages
Book Rating : 4.03/5 ( download)

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Book Synopsis Selfsimilar Processes by : Paul Embrechts

Download or read book Selfsimilar Processes written by Paul Embrechts and published by Princeton University Press. This book was released on 2009-01-10 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: The modeling of stochastic dependence is fundamental for understanding random systems evolving in time. When measured through linear correlation, many of these systems exhibit a slow correlation decay--a phenomenon often referred to as long-memory or long-range dependence. An example of this is the absolute returns of equity data in finance. Selfsimilar stochastic processes (particularly fractional Brownian motion) have long been postulated as a means to model this behavior, and the concept of selfsimilarity for a stochastic process is now proving to be extraordinarily useful. Selfsimilarity translates into the equality in distribution between the process under a linear time change and the same process properly scaled in space, a simple scaling property that yields a remarkably rich theory with far-flung applications. After a short historical overview, this book describes the current state of knowledge about selfsimilar processes and their applications. Concepts, definitions and basic properties are emphasized, giving the reader a road map of the realm of selfsimilarity that allows for further exploration. Such topics as noncentral limit theory, long-range dependence, and operator selfsimilarity are covered alongside statistical estimation, simulation, sample path properties, and stochastic differential equations driven by selfsimilar processes. Numerous references point the reader to current applications. Though the text uses the mathematical language of the theory of stochastic processes, researchers and end-users from such diverse fields as mathematics, physics, biology, telecommunications, finance, econometrics, and environmental science will find it an ideal entry point for studying the already extensive theory and applications of selfsimilarity.

Stochastic Partial Differential Equations With Additive Gaussian Noise - Analysis And Inference

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Publisher : World Scientific
ISBN 13 : 9811264473
Total Pages : 205 pages
Book Rating : 4.74/5 ( download)

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Book Synopsis Stochastic Partial Differential Equations With Additive Gaussian Noise - Analysis And Inference by : Ciprian A Tudor

Download or read book Stochastic Partial Differential Equations With Additive Gaussian Noise - Analysis And Inference written by Ciprian A Tudor and published by World Scientific. This book was released on 2022-10-11 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: The stochastic partial differential equations (SPDEs) arise in many applications of the probability theory. This monograph will focus on two particular (and probably the most known) equations: the stochastic heat equation and the stochastic wave equation.The focus is on the relationship between the solutions to the SPDEs and the fractional Brownian motion (and related processes). An important point of the analysis is the study of the asymptotic behavior of the p-variations of the solutions to the heat or wave equations driven by space-time Gaussian noise or by a Gaussian noise with a non-trivial correlation in space.The book is addressed to public with a reasonable background in probability theory. The idea is to keep it self-contained and avoid using of complex techniques. We also chose to insist on the basic properties of the random noise and to detail the construction of the Wiener integration with respect to them. The intention is to present the proofs complete and detailed.

Simulation of Non-Gaussian Stochastic Processes

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Publisher :
ISBN 13 :
Total Pages : 288 pages
Book Rating : 4.03/5 ( download)

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Book Synopsis Simulation of Non-Gaussian Stochastic Processes by : Yuwei Shi

Download or read book Simulation of Non-Gaussian Stochastic Processes written by Yuwei Shi and published by . This book was released on 2006 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Stable Processes and Related Topics

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Publisher : Springer Science & Business Media
ISBN 13 : 1468467786
Total Pages : 329 pages
Book Rating : 4.89/5 ( download)

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Book Synopsis Stable Processes and Related Topics by : Cambanis

Download or read book Stable Processes and Related Topics written by Cambanis and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Workshop on Stable Processes and Related Topics took place at Cor nell University in January 9-13, 1990, under the sponsorship of the Mathemat ical Sciences Institute. It attracted an international roster of probabilists from Brazil, Japan, Korea, Poland, Germany, Holland and France as well as the U. S. This volume contains a sample of the papers presented at the Workshop. All the papers have been refereed. Gaussian processes have been studied extensively over the last fifty years and form the bedrock of stochastic modeling. Their importance stems from the Central Limit Theorem. They share a number of special properties which facilitates their analysis and makes them particularly suitable to statistical inference. The many properties they share, however, is also the seed of their limitations. What happens in the real world away from the ideal Gaussian model? The non-Gaussian world may contain random processes that are close to the Gaussian. What are appropriate classes of nearly Gaussian models and how typical or robust is the Gaussian model amongst them? Moving further away from normality, what are appropriate non-Gaussian models that are sufficiently different to encompass distinct behavior, yet sufficiently simple to be amenable to efficient statistical inference? The very Central Limit Theorem which provides the fundamental justifi cation for approximate normality, points to stable and other infinitely divisible models. Some of these may be close to and others very different from Gaussian models.

Correlation Theory of Stationary and Related Random Functions

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Publisher : Springer Science & Business Media
ISBN 13 : 1461246288
Total Pages : 267 pages
Book Rating : 4.82/5 ( download)

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Book Synopsis Correlation Theory of Stationary and Related Random Functions by : A.M. Yaglom

Download or read book Correlation Theory of Stationary and Related Random Functions written by A.M. Yaglom and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: Correlation Theory of Stationary and Related Random Functions is an elementary introduction to the most important part of the theory dealing only with the first and second moments of these functions. This theory is a significant part of modern probability theory and offers both intrinsic mathematical interest and many concrete and practical applications. Stationary random functions arise in connection with stationary time series which are so important in many areas of engineering and other applications. This book presents the theory in such a way that it can be understood by readers without specialized mathematical backgrounds, requiring only the knowledge of elementary calculus. The first volume in this two-volume exposition contains the main theory; the supplementary notes and references of the second volume consist of detailed discussions of more specialized questions, some more additional material (which assumes a more thorough mathematical background than the rest of the book) and numerous references to the extensive literature.