Stochastic Models with Power-Law Tails

Stochastic Models with Power-Law Tails

Author: Dariusz Buraczewski

Publisher: Springer

Published: 2016-07-04

Total Pages: 325

ISBN-13: 3319296795

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In this monograph the authors give a systematic approach to the probabilistic properties of the fixed point equation X=AX+B. A probabilistic study of the stochastic recurrence equation X_t=A_tX_{t-1}+B_t for real- and matrix-valued random variables A_t, where (A_t,B_t) constitute an iid sequence, is provided. The classical theory for these equations, including the existence and uniqueness of a stationary solution, the tail behavior with special emphasis on power law behavior, moments and support, is presented. The authors collect recent asymptotic results on extremes, point processes, partial sums (central limit theory with special emphasis on infinite variance stable limit theory), large deviations, in the univariate and multivariate cases, and they further touch on the related topics of smoothing transforms, regularly varying sequences and random iterative systems. The text gives an introduction to the Kesten-Goldie theory for stochastic recurrence equations of the type X_t=A_tX_{t-1}+B_t. It provides the classical results of Kesten, Goldie, Guivarc'h, and others, and gives an overview of recent results on the topic. It presents the state-of-the-art results in the field of affine stochastic recurrence equations and shows relations with non-affine recursions and multivariate regular variation.


Book Synopsis Stochastic Models with Power-Law Tails by : Dariusz Buraczewski

Download or read book Stochastic Models with Power-Law Tails written by Dariusz Buraczewski and published by Springer. This book was released on 2016-07-04 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this monograph the authors give a systematic approach to the probabilistic properties of the fixed point equation X=AX+B. A probabilistic study of the stochastic recurrence equation X_t=A_tX_{t-1}+B_t for real- and matrix-valued random variables A_t, where (A_t,B_t) constitute an iid sequence, is provided. The classical theory for these equations, including the existence and uniqueness of a stationary solution, the tail behavior with special emphasis on power law behavior, moments and support, is presented. The authors collect recent asymptotic results on extremes, point processes, partial sums (central limit theory with special emphasis on infinite variance stable limit theory), large deviations, in the univariate and multivariate cases, and they further touch on the related topics of smoothing transforms, regularly varying sequences and random iterative systems. The text gives an introduction to the Kesten-Goldie theory for stochastic recurrence equations of the type X_t=A_tX_{t-1}+B_t. It provides the classical results of Kesten, Goldie, Guivarc'h, and others, and gives an overview of recent results on the topic. It presents the state-of-the-art results in the field of affine stochastic recurrence equations and shows relations with non-affine recursions and multivariate regular variation.


Stochastic Models for Learning

Stochastic Models for Learning

Author: Robert R. Bush

Publisher:

Published: 1955

Total Pages: 518

ISBN-13:

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Book Synopsis Stochastic Models for Learning by : Robert R. Bush

Download or read book Stochastic Models for Learning written by Robert R. Bush and published by . This book was released on 1955 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt:


Stochastic Models for Fractional Calculus

Stochastic Models for Fractional Calculus

Author: Mark M. Meerschaert

Publisher: Walter de Gruyter GmbH & Co KG

Published: 2019-10-21

Total Pages: 421

ISBN-13: 3110559145

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Fractional calculus is a rapidly growing field of research, at the interface between probability, differential equations, and mathematical physics. It is used to model anomalous diffusion, in which a cloud of particles spreads in a different manner than traditional diffusion. This monograph develops the basic theory of fractional calculus and anomalous diffusion, from the point of view of probability. In this book, we will see how fractional calculus and anomalous diffusion can be understood at a deep and intuitive level, using ideas from probability. It covers basic limit theorems for random variables and random vectors with heavy tails. This includes regular variation, triangular arrays, infinitely divisible laws, random walks, and stochastic process convergence in the Skorokhod topology. The basic ideas of fractional calculus and anomalous diffusion are closely connected with heavy tail limit theorems. Heavy tails are applied in finance, insurance, physics, geophysics, cell biology, ecology, medicine, and computer engineering. The goal of this book is to prepare graduate students in probability for research in the area of fractional calculus, anomalous diffusion, and heavy tails. Many interesting problems in this area remain open. This book will guide the motivated reader to understand the essential background needed to read and unerstand current research papers, and to gain the insights and techniques needed to begin making their own contributions to this rapidly growing field.


Book Synopsis Stochastic Models for Fractional Calculus by : Mark M. Meerschaert

Download or read book Stochastic Models for Fractional Calculus written by Mark M. Meerschaert and published by Walter de Gruyter GmbH & Co KG. This book was released on 2019-10-21 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fractional calculus is a rapidly growing field of research, at the interface between probability, differential equations, and mathematical physics. It is used to model anomalous diffusion, in which a cloud of particles spreads in a different manner than traditional diffusion. This monograph develops the basic theory of fractional calculus and anomalous diffusion, from the point of view of probability. In this book, we will see how fractional calculus and anomalous diffusion can be understood at a deep and intuitive level, using ideas from probability. It covers basic limit theorems for random variables and random vectors with heavy tails. This includes regular variation, triangular arrays, infinitely divisible laws, random walks, and stochastic process convergence in the Skorokhod topology. The basic ideas of fractional calculus and anomalous diffusion are closely connected with heavy tail limit theorems. Heavy tails are applied in finance, insurance, physics, geophysics, cell biology, ecology, medicine, and computer engineering. The goal of this book is to prepare graduate students in probability for research in the area of fractional calculus, anomalous diffusion, and heavy tails. Many interesting problems in this area remain open. This book will guide the motivated reader to understand the essential background needed to read and unerstand current research papers, and to gain the insights and techniques needed to begin making their own contributions to this rapidly growing field.


An Introduction to Heavy-Tailed and Subexponential Distributions

An Introduction to Heavy-Tailed and Subexponential Distributions

Author: Sergey Foss

Publisher: Springer Science & Business Media

Published: 2013-05-21

Total Pages: 167

ISBN-13: 146147101X

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Heavy-tailed probability distributions are an important component in the modeling of many stochastic systems. They are frequently used to accurately model inputs and outputs of computer and data networks and service facilities such as call centers. They are an essential for describing risk processes in finance and also for insurance premia pricing, and such distributions occur naturally in models of epidemiological spread. The class includes distributions with power law tails such as the Pareto, as well as the lognormal and certain Weibull distributions. One of the highlights of this new edition is that it includes problems at the end of each chapter. Chapter 5 is also updated to include interesting applications to queueing theory, risk, and branching processes. New results are presented in a simple, coherent and systematic way. Graduate students as well as modelers in the fields of finance, insurance, network science and environmental studies will find this book to be an essential reference.


Book Synopsis An Introduction to Heavy-Tailed and Subexponential Distributions by : Sergey Foss

Download or read book An Introduction to Heavy-Tailed and Subexponential Distributions written by Sergey Foss and published by Springer Science & Business Media. This book was released on 2013-05-21 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: Heavy-tailed probability distributions are an important component in the modeling of many stochastic systems. They are frequently used to accurately model inputs and outputs of computer and data networks and service facilities such as call centers. They are an essential for describing risk processes in finance and also for insurance premia pricing, and such distributions occur naturally in models of epidemiological spread. The class includes distributions with power law tails such as the Pareto, as well as the lognormal and certain Weibull distributions. One of the highlights of this new edition is that it includes problems at the end of each chapter. Chapter 5 is also updated to include interesting applications to queueing theory, risk, and branching processes. New results are presented in a simple, coherent and systematic way. Graduate students as well as modelers in the fields of finance, insurance, network science and environmental studies will find this book to be an essential reference.


Stochastic Models, Estimation, and Control

Stochastic Models, Estimation, and Control

Author: Peter S. Maybeck

Publisher: Academic Press

Published: 1982-08-25

Total Pages: 311

ISBN-13: 0080960030

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This volume builds upon the foundations set in Volumes 1 and 2. Chapter 13 introduces the basic concepts of stochastic control and dynamic programming as the fundamental means of synthesizing optimal stochastic control laws.


Book Synopsis Stochastic Models, Estimation, and Control by : Peter S. Maybeck

Download or read book Stochastic Models, Estimation, and Control written by Peter S. Maybeck and published by Academic Press. This book was released on 1982-08-25 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume builds upon the foundations set in Volumes 1 and 2. Chapter 13 introduces the basic concepts of stochastic control and dynamic programming as the fundamental means of synthesizing optimal stochastic control laws.


Stochastic Models

Stochastic Models

Author: Source Wikipedia

Publisher: University-Press.org

Published: 2013-09

Total Pages: 94

ISBN-13: 9781230554341

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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Pages: 32. Chapters: Bond fluctuation model, Cellular Potts model, Financial models with long-tailed distributions and volatility clustering, Linear-nonlinear-Poisson cascade model, Monte Carlo molecular modeling, Random neural network, Stochastic investment model, Stochastic modelling (insurance), Substitution model, Wilkie investment model.


Book Synopsis Stochastic Models by : Source Wikipedia

Download or read book Stochastic Models written by Source Wikipedia and published by University-Press.org. This book was released on 2013-09 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt: Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Pages: 32. Chapters: Bond fluctuation model, Cellular Potts model, Financial models with long-tailed distributions and volatility clustering, Linear-nonlinear-Poisson cascade model, Monte Carlo molecular modeling, Random neural network, Stochastic investment model, Stochastic modelling (insurance), Substitution model, Wilkie investment model.


Extreme Value Theory for Time Series

Extreme Value Theory for Time Series

Author: Thomas Mikosch

Publisher: Springer

Published: 2024-07-29

Total Pages: 0

ISBN-13: 9783031591556

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This book deals with extreme value theory for univariate and multivariate time series models characterized by power-law tails. These include the classical ARMA models with heavy-tailed noise and financial econometrics models such as the GARCH and stochastic volatility models. Rigorous descriptions of power-law tails are provided through the concept of regular variation. Several chapters are devoted to the exploration of regularly varying structures. The remaining chapters focus on the impact of heavy tails on time series, including the study of extremal cluster phenomena through point process techniques. A major part of the book investigates how extremal dependence alters the limit structure of sample means, maxima, order statistics, sample autocorrelations. This text illuminates the theory through hundreds of examples and as many graphs showcasing its applications to real-life financial and simulated data. The book can serve as a text for PhD and Master courses on applied probability, extreme value theory, and time series analysis. It is a unique reference source for the heavy-tail modeler. Its reference quality is enhanced by an exhaustive bibliography, annotated by notes and comments making the book broadly and easily accessible.


Book Synopsis Extreme Value Theory for Time Series by : Thomas Mikosch

Download or read book Extreme Value Theory for Time Series written by Thomas Mikosch and published by Springer. This book was released on 2024-07-29 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with extreme value theory for univariate and multivariate time series models characterized by power-law tails. These include the classical ARMA models with heavy-tailed noise and financial econometrics models such as the GARCH and stochastic volatility models. Rigorous descriptions of power-law tails are provided through the concept of regular variation. Several chapters are devoted to the exploration of regularly varying structures. The remaining chapters focus on the impact of heavy tails on time series, including the study of extremal cluster phenomena through point process techniques. A major part of the book investigates how extremal dependence alters the limit structure of sample means, maxima, order statistics, sample autocorrelations. This text illuminates the theory through hundreds of examples and as many graphs showcasing its applications to real-life financial and simulated data. The book can serve as a text for PhD and Master courses on applied probability, extreme value theory, and time series analysis. It is a unique reference source for the heavy-tail modeler. Its reference quality is enhanced by an exhaustive bibliography, annotated by notes and comments making the book broadly and easily accessible.


Tail of the Stationary Solution of the Stochastic Equation

Tail of the Stationary Solution of the Stochastic Equation

Author: Benoîte de Saporta

Publisher:

Published: 2018

Total Pages: 27

ISBN-13:

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In this paper, we deal with the real stochastic difference equation = + , ∈ Z, where the sequence () is a finite state space Markov chain. By means of the renewal theory, we give a precise description of the situation where the tail of its stationary solution exhibits power law behavior.


Book Synopsis Tail of the Stationary Solution of the Stochastic Equation by : Benoîte de Saporta

Download or read book Tail of the Stationary Solution of the Stochastic Equation written by Benoîte de Saporta and published by . This book was released on 2018 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we deal with the real stochastic difference equation = + , ∈ Z, where the sequence () is a finite state space Markov chain. By means of the renewal theory, we give a precise description of the situation where the tail of its stationary solution exhibits power law behavior.


Tail Behaviour for Stationary Distributions for Two-dimensional Stochastic Models [microform]

Tail Behaviour for Stationary Distributions for Two-dimensional Stochastic Models [microform]

Author: Lani Haque

Publisher: National Library of Canada = Bibliothèque nationale du Canada

Published: 2004

Total Pages: 358

ISBN-13: 9780612898912

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Book Synopsis Tail Behaviour for Stationary Distributions for Two-dimensional Stochastic Models [microform] by : Lani Haque

Download or read book Tail Behaviour for Stationary Distributions for Two-dimensional Stochastic Models [microform] written by Lani Haque and published by National Library of Canada = Bibliothèque nationale du Canada. This book was released on 2004 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt:


Stochastic Pursuit Models

Stochastic Pursuit Models

Author: Kellan R. Toman

Publisher:

Published: 2021

Total Pages: 88

ISBN-13:

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Recent years have seen an increase of evidence of systems driven by diffusive processes that exhibit mixed linear and anomalous diffusive regimes, typically in the form of an anomalous to normal transition in time. Despite showing many characteristics reminiscent of anomalous diffusion, the density profiles of these systems seem to carry over exponential tails in strong contrast to power-laws. Inspired by the simple idea of a driven particle undergoing Brownian diffusion while simultaneously pursuing another diffusive particle, we develop a model of stochastic pursuit that exhibits transient anomalous features while maintaining key normal diffusive components. Specifically, we show: a) the model is capable of capturing transient sub-diffusion, super-diffusion and pure super-diffusion depending on the parameters, b) the orientation auto-correlation function of the model exhibits stretched-exponential behavior, c) hitting (catching) times are Inverse-Gaussian distributed, and d) the distance between the two particles satisfies the dry friction equation. Extensions of the model to higher dimensions are also presented, where the properties of the model are shown to have strong dimension dependence. As an application, we apply the stochastic pursuit-evasion model to foraging theory, and show how the model fits well with experimental data from cell-motility.


Book Synopsis Stochastic Pursuit Models by : Kellan R. Toman

Download or read book Stochastic Pursuit Models written by Kellan R. Toman and published by . This book was released on 2021 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent years have seen an increase of evidence of systems driven by diffusive processes that exhibit mixed linear and anomalous diffusive regimes, typically in the form of an anomalous to normal transition in time. Despite showing many characteristics reminiscent of anomalous diffusion, the density profiles of these systems seem to carry over exponential tails in strong contrast to power-laws. Inspired by the simple idea of a driven particle undergoing Brownian diffusion while simultaneously pursuing another diffusive particle, we develop a model of stochastic pursuit that exhibits transient anomalous features while maintaining key normal diffusive components. Specifically, we show: a) the model is capable of capturing transient sub-diffusion, super-diffusion and pure super-diffusion depending on the parameters, b) the orientation auto-correlation function of the model exhibits stretched-exponential behavior, c) hitting (catching) times are Inverse-Gaussian distributed, and d) the distance between the two particles satisfies the dry friction equation. Extensions of the model to higher dimensions are also presented, where the properties of the model are shown to have strong dimension dependence. As an application, we apply the stochastic pursuit-evasion model to foraging theory, and show how the model fits well with experimental data from cell-motility.