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Extremes in Random Fields

Author: Benjamin Yakir

Publisher: John Wiley & Sons

Published: 2013-08-01

Total Pages: 192

ISBN-13: 1118720628

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Presents a useful new technique for analyzing the extreme-value behaviour of random fields Modern science typically involves the analysis of increasingly complex data. The extreme values that emerge in the statistical analysis of complex data are often of particular interest. This book focuses on the analytical approximations of the statistical significance of extreme values. Several relatively complex applications of the technique to problems that emerge in practical situations are presented. All the examples are difficult to analyze using classical methods, and as a result, the author presents a novel technique, designed to be more accessible to the user. Extreme value analysis is widely applied in areas such as operational research, bioinformatics, computer science, finance and many other disciplines. This book will be useful for scientists, engineers and advanced graduate students who need to develop their own statistical tools for the analysis of their data. Whilst this book may not provide the reader with the specific answer it will inspire them to rethink their problem in the context of random fields, apply the method, and produce a solution.

Book Synopsis Extremes in Random Fields by : Benjamin Yakir

Download or read book Extremes in Random Fields written by Benjamin Yakir and published by John Wiley & Sons. This book was released on 2013-08-01 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents a useful new technique for analyzing the extreme-value behaviour of random fields Modern science typically involves the analysis of increasingly complex data. The extreme values that emerge in the statistical analysis of complex data are often of particular interest. This book focuses on the analytical approximations of the statistical significance of extreme values. Several relatively complex applications of the technique to problems that emerge in practical situations are presented. All the examples are difficult to analyze using classical methods, and as a result, the author presents a novel technique, designed to be more accessible to the user. Extreme value analysis is widely applied in areas such as operational research, bioinformatics, computer science, finance and many other disciplines. This book will be useful for scientists, engineers and advanced graduate students who need to develop their own statistical tools for the analysis of their data. Whilst this book may not provide the reader with the specific answer it will inspire them to rethink their problem in the context of random fields, apply the method, and produce a solution.

Level Sets and Extrema of Random Processes and Fields

Author: Jean-Marc Azais

Publisher: John Wiley & Sons

Published: 2009-02-17

Total Pages: 407

ISBN-13: 0470434635

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A timely and comprehensive treatment of random field theory with applications across diverse areas of study Level Sets and Extrema of Random Processes and Fields discusses how to understand the properties of the level sets of paths as well as how to compute the probability distribution of its extremal values, which are two general classes of problems that arise in the study of random processes and fields and in related applications. This book provides a unified and accessible approach to these two topics and their relationship to classical theory and Gaussian processes and fields, and the most modern research findings are also discussed. The authors begin with an introduction to the basic concepts of stochastic processes, including a modern review of Gaussian fields and their classical inequalities. Subsequent chapters are devoted to Rice formulas, regularity properties, and recent results on the tails of the distribution of the maximum. Finally, applications of random fields to various areas of mathematics are provided, specifically to systems of random equations and condition numbers of random matrices. Throughout the book, applications are illustrated from various areas of study such as statistics, genomics, and oceanography while other results are relevant to econometrics, engineering, and mathematical physics. The presented material is reinforced by end-of-chapter exercises that range in varying degrees of difficulty. Most fundamental topics are addressed in the book, and an extensive, up-to-date bibliography directs readers to existing literature for further study. Level Sets and Extrema of Random Processes and Fields is an excellent book for courses on probability theory, spatial statistics, Gaussian fields, and probabilistic methods in real computation at the upper-undergraduate and graduate levels. It is also a valuable reference for professionals in mathematics and applied fields such as statistics, engineering, econometrics, mathematical physics, and biology.

Book Synopsis Level Sets and Extrema of Random Processes and Fields by : Jean-Marc Azais

Download or read book Level Sets and Extrema of Random Processes and Fields written by Jean-Marc Azais and published by John Wiley & Sons. This book was released on 2009-02-17 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt: A timely and comprehensive treatment of random field theory with applications across diverse areas of study Level Sets and Extrema of Random Processes and Fields discusses how to understand the properties of the level sets of paths as well as how to compute the probability distribution of its extremal values, which are two general classes of problems that arise in the study of random processes and fields and in related applications. This book provides a unified and accessible approach to these two topics and their relationship to classical theory and Gaussian processes and fields, and the most modern research findings are also discussed. The authors begin with an introduction to the basic concepts of stochastic processes, including a modern review of Gaussian fields and their classical inequalities. Subsequent chapters are devoted to Rice formulas, regularity properties, and recent results on the tails of the distribution of the maximum. Finally, applications of random fields to various areas of mathematics are provided, specifically to systems of random equations and condition numbers of random matrices. Throughout the book, applications are illustrated from various areas of study such as statistics, genomics, and oceanography while other results are relevant to econometrics, engineering, and mathematical physics. The presented material is reinforced by end-of-chapter exercises that range in varying degrees of difficulty. Most fundamental topics are addressed in the book, and an extensive, up-to-date bibliography directs readers to existing literature for further study. Level Sets and Extrema of Random Processes and Fields is an excellent book for courses on probability theory, spatial statistics, Gaussian fields, and probabilistic methods in real computation at the upper-undergraduate and graduate levels. It is also a valuable reference for professionals in mathematics and applied fields such as statistics, engineering, econometrics, mathematical physics, and biology.

Random Fields and Geometry

Author: R. J. Adler

Publisher: Springer Science & Business Media

Published: 2009-01-29

Total Pages: 455

ISBN-13: 0387481168

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This monograph is devoted to a completely new approach to geometric problems arising in the study of random fields. The groundbreaking material in Part III, for which the background is carefully prepared in Parts I and II, is of both theoretical and practical importance, and striking in the way in which problems arising in geometry and probability are beautifully intertwined. "Random Fields and Geometry" will be useful for probabilists and statisticians, and for theoretical and applied mathematicians who wish to learn about new relationships between geometry and probability. It will be helpful for graduate students in a classroom setting, or for self-study. Finally, this text will serve as a basic reference for all those interested in the companion volume of the applications of the theory.

Book Synopsis Random Fields and Geometry by : R. J. Adler

Download or read book Random Fields and Geometry written by R. J. Adler and published by Springer Science & Business Media. This book was released on 2009-01-29 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph is devoted to a completely new approach to geometric problems arising in the study of random fields. The groundbreaking material in Part III, for which the background is carefully prepared in Parts I and II, is of both theoretical and practical importance, and striking in the way in which problems arising in geometry and probability are beautifully intertwined. "Random Fields and Geometry" will be useful for probabilists and statisticians, and for theoretical and applied mathematicians who wish to learn about new relationships between geometry and probability. It will be helpful for graduate students in a classroom setting, or for self-study. Finally, this text will serve as a basic reference for all those interested in the companion volume of the applications of the theory.

Applied Extreme Value Statistics

Author: Arvid Naess

Publisher: Springer Nature

Published:

Total Pages: 277

ISBN-13: 3031607694

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Book Synopsis Applied Extreme Value Statistics by : Arvid Naess

Download or read book Applied Extreme Value Statistics written by Arvid Naess and published by Springer Nature. This book was released on with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Random Fields

Author: Erik Vanmarcke

Publisher: World Scientific

Published: 2010

Total Pages: 363

ISBN-13: 9812562974

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Random variation is a fact of life that provides substance to a wide range of problems in the sciences, engineering, and economics. There is a growing need in diverse disciplines to model complex patterns of variation and interdependence using random fields, as both deterministic treatment and conventional statistics are often insufficient. An ideal random field model will capture key features of complex random phenomena in terms of a minimum number of physically meaningful and experimentally accessible parameters. This volume, a revised and expanded edition of an acclaimed book first published by the M I T Press, offers a synthesis of methods to describe and analyze and, where appropriate, predict and control random fields. There is much new material, covering both theory and applications, notably on a class of probability distributions derived from quantum mechanics, relevant to stochastic modeling in fields such as cosmology, biology and system reliability, and on discrete-unit or agent-based random processes.Random Fields is self-contained and unified in presentation. The first edition was found, in a review in EOS (American Geophysical Union) to be ?both technically interesting and a pleasure to read ? the presentation is clear and the book should be useful to almost anyone who uses random processes to solve problems in engineering or science ? and (there is) continued emphasis on describing the mathematics in physical terms.?

Book Synopsis Random Fields by : Erik Vanmarcke

Download or read book Random Fields written by Erik Vanmarcke and published by World Scientific. This book was released on 2010 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: Random variation is a fact of life that provides substance to a wide range of problems in the sciences, engineering, and economics. There is a growing need in diverse disciplines to model complex patterns of variation and interdependence using random fields, as both deterministic treatment and conventional statistics are often insufficient. An ideal random field model will capture key features of complex random phenomena in terms of a minimum number of physically meaningful and experimentally accessible parameters. This volume, a revised and expanded edition of an acclaimed book first published by the M I T Press, offers a synthesis of methods to describe and analyze and, where appropriate, predict and control random fields. There is much new material, covering both theory and applications, notably on a class of probability distributions derived from quantum mechanics, relevant to stochastic modeling in fields such as cosmology, biology and system reliability, and on discrete-unit or agent-based random processes.Random Fields is self-contained and unified in presentation. The first edition was found, in a review in EOS (American Geophysical Union) to be ?both technically interesting and a pleasure to read ? the presentation is clear and the book should be useful to almost anyone who uses random processes to solve problems in engineering or science ? and (there is) continued emphasis on describing the mathematics in physical terms.?

Advances in Regression, Survival Analysis, Extreme Values, Markov Processes and Other Statistical Applications

Author: João Lita da Silva

Publisher: Springer Science & Business Media

Published: 2013-06-14

Total Pages: 465

ISBN-13: 3642349048

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This volume of the Selected Papers from Portugal is a product of the Seventeenth Congress of the Portuguese Statistical Society, held at the beautiful resort seaside city of Sesimbra, Portugal, from September 30 to October 3, 2009. It covers a broad scope of theoretical, methodological as well as application-oriented articles in domains such as: Linear Models and Regression, Survival Analysis, Extreme Value Theory, Statistics of Diffusions, Markov Processes and other Statistical Applications.

Book Synopsis Advances in Regression, Survival Analysis, Extreme Values, Markov Processes and Other Statistical Applications by : João Lita da Silva

Download or read book Advances in Regression, Survival Analysis, Extreme Values, Markov Processes and Other Statistical Applications written by João Lita da Silva and published by Springer Science & Business Media. This book was released on 2013-06-14 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume of the Selected Papers from Portugal is a product of the Seventeenth Congress of the Portuguese Statistical Society, held at the beautiful resort seaside city of Sesimbra, Portugal, from September 30 to October 3, 2009. It covers a broad scope of theoretical, methodological as well as application-oriented articles in domains such as: Linear Models and Regression, Survival Analysis, Extreme Value Theory, Statistics of Diffusions, Markov Processes and other Statistical Applications.

Random Fields for Spatial Data Modeling

Author: Dionissios T. Hristopulos

Publisher: Springer Nature

Published: 2020-02-17

Total Pages: 884

ISBN-13: 9402419187

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This book provides an inter-disciplinary introduction to the theory of random fields and its applications. Spatial models and spatial data analysis are integral parts of many scientific and engineering disciplines. Random fields provide a general theoretical framework for the development of spatial models and their applications in data analysis. The contents of the book include topics from classical statistics and random field theory (regression models, Gaussian random fields, stationarity, correlation functions) spatial statistics (variogram estimation, model inference, kriging-based prediction) and statistical physics (fractals, Ising model, simulated annealing, maximum entropy, functional integral representations, perturbation and variational methods). The book also explores links between random fields, Gaussian processes and neural networks used in machine learning. Connections with applied mathematics are highlighted by means of models based on stochastic partial differential equations. An interlude on autoregressive time series provides useful lower-dimensional analogies and a connection with the classical linear harmonic oscillator. Other chapters focus on non-Gaussian random fields and stochastic simulation methods. The book also presents results based on the author’s research on Spartan random fields that were inspired by statistical field theories originating in physics. The equivalence of the one-dimensional Spartan random field model with the classical, linear, damped harmonic oscillator driven by white noise is highlighted. Ideas with potentially significant computational gains for the processing of big spatial data are presented and discussed. The final chapter concludes with a description of the Karhunen-Loève expansion of the Spartan model. The book will appeal to engineers, physicists, and geoscientists whose research involves spatial models or spatial data analysis. Anyone with background in probability and statistics can read at least parts of the book. Some chapters will be easier to understand by readers familiar with differential equations and Fourier transforms.

Book Synopsis Random Fields for Spatial Data Modeling by : Dionissios T. Hristopulos

Download or read book Random Fields for Spatial Data Modeling written by Dionissios T. Hristopulos and published by Springer Nature. This book was released on 2020-02-17 with total page 884 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an inter-disciplinary introduction to the theory of random fields and its applications. Spatial models and spatial data analysis are integral parts of many scientific and engineering disciplines. Random fields provide a general theoretical framework for the development of spatial models and their applications in data analysis. The contents of the book include topics from classical statistics and random field theory (regression models, Gaussian random fields, stationarity, correlation functions) spatial statistics (variogram estimation, model inference, kriging-based prediction) and statistical physics (fractals, Ising model, simulated annealing, maximum entropy, functional integral representations, perturbation and variational methods). The book also explores links between random fields, Gaussian processes and neural networks used in machine learning. Connections with applied mathematics are highlighted by means of models based on stochastic partial differential equations. An interlude on autoregressive time series provides useful lower-dimensional analogies and a connection with the classical linear harmonic oscillator. Other chapters focus on non-Gaussian random fields and stochastic simulation methods. The book also presents results based on the author’s research on Spartan random fields that were inspired by statistical field theories originating in physics. The equivalence of the one-dimensional Spartan random field model with the classical, linear, damped harmonic oscillator driven by white noise is highlighted. Ideas with potentially significant computational gains for the processing of big spatial data are presented and discussed. The final chapter concludes with a description of the Karhunen-Loève expansion of the Spartan model. The book will appeal to engineers, physicists, and geoscientists whose research involves spatial models or spatial data analysis. Anyone with background in probability and statistics can read at least parts of the book. Some chapters will be easier to understand by readers familiar with differential equations and Fourier transforms.

Sojourns And Extremes of Stochastic Processes

Author: Simeon Berman

Publisher: CRC Press

Published: 2017-07-12

Total Pages: 315

ISBN-13: 1351415646

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Sojourns and Extremes of Stochastic Processes is a research monograph in the area of probability theory. During the past thirty years Berman has made many contributions to the theory of the extreme values and sojourn times of the sample functions of broad classes of stochastic processes. These processes arise in theoretical and applied models, and are presented here in a unified exposition.

Book Synopsis Sojourns And Extremes of Stochastic Processes by : Simeon Berman

Download or read book Sojourns And Extremes of Stochastic Processes written by Simeon Berman and published by CRC Press. This book was released on 2017-07-12 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sojourns and Extremes of Stochastic Processes is a research monograph in the area of probability theory. During the past thirty years Berman has made many contributions to the theory of the extreme values and sojourn times of the sample functions of broad classes of stochastic processes. These processes arise in theoretical and applied models, and are presented here in a unified exposition.

Extreme Value Modeling and Risk Analysis

Author: Dipak K. Dey

Publisher: CRC Press

Published: 2016-01-06

Total Pages: 538

ISBN-13: 1498701310

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Extreme Value Modeling and Risk Analysis: Methods and Applications presents a broad overview of statistical modeling of extreme events along with the most recent methodologies and various applications. The book brings together background material and advanced topics, eliminating the need to sort through the massive amount of literature on the subje

Book Synopsis Extreme Value Modeling and Risk Analysis by : Dipak K. Dey

Download or read book Extreme Value Modeling and Risk Analysis written by Dipak K. Dey and published by CRC Press. This book was released on 2016-01-06 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: Extreme Value Modeling and Risk Analysis: Methods and Applications presents a broad overview of statistical modeling of extreme events along with the most recent methodologies and various applications. The book brings together background material and advanced topics, eliminating the need to sort through the massive amount of literature on the subje

Stochastic Processes and Related Topics

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.

Book Synopsis Stochastic Processes and Related Topics by : Stamatis Cambanis

Download or read book Stochastic Processes and Related Topics written by Stamatis Cambanis and published by Springer Science & Business Media. This book was released on 1998 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.