Minimum Distance Estimation for Diffusion Random Fields PDF Download
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Author: Yu. A. Kutoyants
Publisher:
ISBN:
Category :
Languages : en
Pages : 15
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Book Description
Author: Yu. A. Kutoyants
Publisher:
ISBN:
Category :
Languages : en
Pages : 15
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Book Description
Author: Yury A. Kutoyants
Publisher: Springer Science & Business Media
ISBN: 144713866X
Category : Mathematics
Languages : en
Pages : 493
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Book Description
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.
Author: Erwin Bolthausen
Publisher: Birkhäuser
ISBN: 3034870264
Category : Mathematics
Languages : en
Pages : 392
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Book Description
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.
Author: Alexander G Ramm
Publisher: World Scientific
ISBN: 9814479098
Category : Mathematics
Languages : en
Pages : 388
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Book Description
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.
Author: Hans M. Dietz
Publisher:
ISBN:
Category :
Languages : de
Pages : 18
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Book Description
Author: Jaya P. N. Bishwal
Publisher: Springer
ISBN: 3540744487
Category : Mathematics
Languages : en
Pages : 271
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Book Description
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.
Author:
Publisher:
ISBN:
Category : Engineering mathematics
Languages : en
Pages : 534
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Book Description
Author: Jagadis Chandra Misra
Publisher: World Scientific
ISBN: 9814488046
Category : Mathematics
Languages : en
Pages : 571
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Book Description
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.
Author: Xavier Guyon
Publisher: Springer Science & Business Media
ISBN: 9780387944289
Category : Mathematics
Languages : en
Pages : 294
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Book Description
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.
Author: Luc Florack
Publisher: Springer Science & Business Media
ISBN: 1447123522
Category : Mathematics
Languages : en
Pages : 321
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Book Description
Mathematical Methods for Signal and Image Analysis and Representation presents the mathematical methodology for generic image analysis tasks. In the context of this book an image may be any m-dimensional empirical signal living on an n-dimensional smooth manifold (typically, but not necessarily, a subset of spacetime). The existing literature on image methodology is rather scattered and often limited to either a deterministic or a statistical point of view. In contrast, this book brings together these seemingly different points of view in order to stress their conceptual relations and formal analogies. Furthermore, it does not focus on specific applications, although some are detailed for the sake of illustration, but on the methodological frameworks on which such applications are built, making it an ideal companion for those seeking a rigorous methodological basis for specific algorithms as well as for those interested in the fundamental methodology per se. Covering many topics at the forefront of current research, including anisotropic diffusion filtering of tensor fields, this book will be of particular interest to graduate and postgraduate students and researchers in the fields of computer vision, medical imaging and visual perception.
