Statistical Inference for Ergodic Diffusion Processes
Statistical Inference for Ergodic Diffusion Processes

Author: Yury A. Kutoyants

Publisher: Springer Science & Business Media

Published: 2013-03-09

Total Pages: 493

ISBN-13: 144713866X

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The first book in inference for stochastic processes from a statistical, rather than a probabilistic, perspective. It provides a systematic exposition of theoretical results from over ten years of mathematical literature and presents, for the first time in book form, many new techniques and approaches.

Seminar on Stochastic Analysis, Random Fields and Applications
Seminar on Stochastic Analysis, Random Fields and Applications

Author: Erwin Bolthausen

Publisher: Birkhäuser

Published: 2012-12-06

Total Pages: 392

ISBN-13: 3034870264

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Pure and applied stochastic analysis and random fields form the subject of this book. The collection of articles on these topics represent the state of the art of the research in the field, with particular attention being devoted to stochastic models in finance. Some are review articles, others are original papers; taken together, they will apprise the reader of much of the current activity in the area.

Random Fields Estimation
Random Fields Estimation

Author: Alexander G Ramm

Publisher: World Scientific

Published: 2005-11-18

Total Pages: 388

ISBN-13: 9814479098

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This book contains a novel theory of random fields estimation of Wiener type, developed originally by the author and presented here. No assumption about the Gaussian or Markovian nature of the fields are made. The theory, constructed entirely within the framework of covariance theory, is based on a detailed analytical study of a new class of multidimensional integral equations basic in estimation theory.This book is suitable for graduate courses in random fields estimation. It can also be used in courses in functional analysis, numerical analysis, integral equations, and scattering theory.

Parameter Estimation in Stochastic Differential Equations
Parameter Estimation in Stochastic Differential Equations

Author: Jaya P. N. Bishwal

Publisher: Springer

Published: 2007-09-26

Total Pages: 271

ISBN-13: 3540744487

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Parameter estimation in stochastic differential equations and stochastic partial differential equations is the science, art and technology of modeling complex phenomena. The subject has attracted researchers from several areas of mathematics. This volume presents the estimation of the unknown parameters in the corresponding continuous models based on continuous and discrete observations and examines extensively maximum likelihood, minimum contrast and Bayesian methods.

Random Fields on a Network
Random Fields on a Network

Author: Xavier Guyon

Publisher: Springer Science & Business Media

Published: 1995-06-23

Total Pages: 294

ISBN-13: 9780387944289

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The theory of spatial models over lattices, or random fields as they are known, has developed significantly over recent years. This book provides a graduate-level introduction to the subject which assumes only a basic knowledge of probability and statistics, finite Markov chains, and the spectral theory of second-order processes. A particular strength of this book is its emphasis on examples - both to motivate the theory which is being developed, and to demonstrate the applications which range from statistical mechanics to image analysis and from statistics to stochastic algorithms.

Uncertainty and Optimality
Uncertainty and Optimality

Author: J. C. Misra

Publisher: World Scientific

Published: 2002

Total Pages: 571

ISBN-13: 9812380825

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This book deals with different modern topics in probability, statistics and operations research. It has been written lucidly in a novel way. Wherever necessary, the theory is explained in great detail, with suitable illustrations. Numerous references are given, so that young researchers who want to start their work in a particular area will benefit immensely from the book.The contributors are distinguished statisticians and operations research experts from all over the world.

Limit Theorems for Random Fields with Singular Spectrum
Limit Theorems for Random Fields with Singular Spectrum

Author: Nicolai Leonenko

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 410

ISBN-13: 9401146071

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This book presents limit theorems for nonlinear functionals of random fields with singular spectrum on the basis of various asymptotic expansions. The first chapter treats basic concepts of the spectral theory of random fields, some important examples of random processes and fields with singular spectrum, and Tauberian and Abelian theorems for covariance function of long-memory random fields. Chapter 2 is devoted to limit theorems for spherical averages of nonlinear transformations of Gaussian and chi-square random fields. Chapter 3 summarises some limit theorems for geometric type functionals of random fields. Limit theorems for the solutions of Burgers' equation with random data via parabolic and hyperbolic rescaling are demonstrated in Chapter 4. Lastly, Chapter 5 deals with some problems for statistical analysis of random fields with singular spectrum. Audience: This book will be of interest to mathematicians who use random fields in engineering or other applications.