Stable Processes and Related Topics

Stable Processes and Related Topics PDF

Author: Cambanis

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 329

ISBN-13: 1468467786

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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.

Potential Analysis of Stable Processes and its Extensions

Potential Analysis of Stable Processes and its Extensions PDF

Author: Krzysztof Bogdan

Publisher: Springer Science & Business Media

Published: 2009-07-14

Total Pages: 200

ISBN-13: 3642021417

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Stable Lévy processes and related stochastic processes play an important role in stochastic modelling in applied sciences, in particular in financial mathematics. This book is about the potential theory of stable stochastic processes. It also deals with related topics, such as the subordinate Brownian motions (including the relativistic process) and Feynman–Kac semigroups generated by certain Schrödinger operators. The authors focus on classes of stable and related processes that contain the Brownian motion as a special case. This is the first book devoted to the probabilistic potential theory of stable stochastic processes, and, from the analytical point of view, of the fractional Laplacian. The introduction is accessible to non-specialists and provides a general presentation of the fundamental objects of the theory. Besides recent and deep scientific results the book also provides a didactic approach to its topic, as all chapters have been tested on a wide audience, including young mathematicians at a CNRS/HARP Workshop, Angers 2006. The reader will gain insight into the modern theory of stable and related processes and their potential analysis with a theoretical motivation for the study of their fine properties.

Stochastic Processes and Related Topics

Stochastic Processes and Related Topics PDF

Author: Stamatis Cambanis

Publisher: Springer Science & Business Media

Published: 1998

Total Pages: 418

ISBN-13: 9780817639983

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Spectral Representation and Structure of Stable Self-Similar Processes.- Three Elementary Proofs of the Central Limit Theorem with Applications to Random Sums.- Almost Everywhere Convergence and SLLN Under Rearrangements.- Sufficient Conditions for the Existence of Conditional Moments of Stable Random Variables.- How Heavy are the Tails of a Stationary HARCH(k) Process? A Study of the Moments.- Use of Stochastic Comparisons in Communication Networks.- On the Conditional Variance-Covariance of Stable Random Vectors, II.- Interacting Particle Approximation for Fractal Burgers Equation.- Optimal Transformations for Prediction in Continuous-Time Stochastic Processes.- Algebraic Methods Toward Higher-Order Probability Inequalities.- Comparison and Deviation from a Representation Formula.- Components of the Strong Markov Property.- The Russian Options.- Cycle Representations of Markov Processes: An Application to Rotational Partitions.- On Extreme Values in Stationary Random Fields.- Norming Operators for Operator-Self-Similar Processes.- Multivariate Probability Density and Regression Functions Estimation of Continuous-time Stationary Processes from Discrete-time Data.- Tracing the Path of a Wright-Fisher Process with One-way Mutation in the Case of a Large Deviation.- A Distribution Inequality for Martingales with Bounded Symmetric Differences.- Moment Comparison of Multilinear Forms in Stable and Semistable Random Variables with Application to Semistable Multiple Integrals.- Global Dependency Measure for Sets of Random Elements: "The Italian Problem" and Some Consequences.

Stable Non-Gaussian Random Processes

Stable Non-Gaussian Random Processes PDF

Author: Gennady Samoradnitsky

Publisher: Routledge

Published: 2017-11-22

Total Pages: 632

ISBN-13: 1351414801

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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.

Stochastic Processes and Related Topics

Stochastic Processes and Related Topics PDF

Author: Ioannis Karatzas

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 391

ISBN-13: 1461220300

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In the last twenty years extensive research has been devoted to a better understanding of the stable and other closely related infinitely divisible mod els. Stamatis Cambanis, a distinguished educator and researcher, played a special leadership role in the development of these research efforts, particu larly related to stable processes from the early seventies until his untimely death in April '95. This commemorative volume consists of a collection of research articles devoted to reviewing the state of the art of this and other rapidly developing research and to explore new directions of research in these fields. The volume is a tribute to the Life and Work of Stamatis by his students, friends, and colleagues whose personal and professional lives he has deeply touched through his generous insights and dedication to his profession. Before the idea of this volume was conceived, two conferences were held in the memory of Stamatis. The first was organized by the University of Athens and the Athens University of Economics and was held in Athens during December 18-19, 1995. The second was a significant part of a Spe cial IMS meeting held at the campus of the University of North Carolina at Chapel Hill during October 17-19, 1996. It is the selfless effort of sev eral people that brought about these conferences. We believe that this is an appropriate place to acknowledge their effort; and on behalf of all the participants, we extend sincere thanks to all these persons.

Large Deviations for Stochastic Processes

Large Deviations for Stochastic Processes PDF

Author: Jin Feng

Publisher: American Mathematical Soc.

Published: 2006

Total Pages: 426

ISBN-13: 0821841459

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The book is devoted to the results on large deviations for a class of stochastic processes. Following an introduction and overview, the material is presented in three parts. Part 1 gives necessary and sufficient conditions for exponential tightness that are analogous to conditions for tightness in the theory of weak convergence. Part 2 focuses on Markov processes in metric spaces. For a sequence of such processes, convergence of Fleming's logarithmically transformed nonlinear semigroups is shown to imply the large deviation principle in a manner analogous to the use of convergence of linear semigroups in weak convergence. Viscosity solution methods provide applicable conditions for the necessary convergence. Part 3 discusses methods for verifying the comparison principle for viscosity solutions and applies the general theory to obtain a variety of new and known results on large deviations for Markov processes. In examples concerning infinite dimensional state spaces, new comparison principles are derived for a class of Hamilton-Jacobi equations in Hilbert spaces and in spaces of probability measures.

Stable Lévy Processes via Lamperti-Type Representations

Stable Lévy Processes via Lamperti-Type Representations PDF

Author: Andreas E. Kyprianou

Publisher: Cambridge University Press

Published: 2022-04-07

Total Pages: 486

ISBN-13: 1108572162

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Stable Lévy processes lie at the intersection of Lévy processes and self-similar Markov processes. Processes in the latter class enjoy a Lamperti-type representation as the space-time path transformation of so-called Markov additive processes (MAPs). This completely new mathematical treatment takes advantage of the fact that the underlying MAP for stable processes can be explicitly described in one dimension and semi-explicitly described in higher dimensions, and uses this approach to catalogue a large number of explicit results describing the path fluctuations of stable Lévy processes in one and higher dimensions. Written for graduate students and researchers in the field, this book systemically establishes many classical results as well as presenting many recent results appearing in the last decade, including previously unpublished material. Topics explored include first hitting laws for a variety of sets, path conditionings, law-preserving path transformations, the distribution of extremal points, growth envelopes and winding behaviour.

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