Gaussian Process Regression Analysis for Functional Data, Shi, Jian Qing
Автор: Gramacy, Robert B. (virginia Tech Department Of Statistics, Usa) Название: Surrogates ISBN: 0367415429 ISBN-13(EAN): 9780367415426 Издательство: Taylor&Francis Рейтинг: Цена: 17609.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Surrogates is a graduate textbook, on topics at the interface between machine learning,spatial statistics,computer simulation,meta-modeling,design of experiments,and optimization. Experimentation through simulation,management of dynamic processes,online and real-time analysis,automation and practical application are at the forefront.
Автор: Hu Yaozhong Название: Analysis on Gaussian Spaces ISBN: 9813142170 ISBN-13(EAN): 9789813142176 Издательство: World Scientific Publishing Цена: 24552.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 'Written by a well-known expert in fractional stochastic calculus, this book offers a comprehensive overview of Gaussian analysis, with particular emphasis on nonlinear Gaussian functionals. In addition, it covers some topics that are not frequently encountered in other treatments, such as Littlewood-Paley-Stein, etc. This coverage makes the book a valuable addition to the literature. Many results presented in this book were hitherto available only in the research literature in the form of research papers by the author and his co-authors.'Mathematical Reviews ClippingsAnalysis of functions on the finite dimensional Euclidean space with respect to the Lebesgue measure is fundamental in mathematics. The extension to infinite dimension is a great challenge due to the lack of Lebesgue measure on infinite dimensional space. Instead the most popular measure used in infinite dimensional space is the Gaussian measure, which has been unified under the terminology of 'abstract Wiener space'.Out of the large amount of work on this topic, this book presents some fundamental results plus recent progress. We shall present some results on the Gaussian space itself such as the Brunn-Minkowski inequality, Small ball estimates, large tail estimates. The majority part of this book is devoted to the analysis of nonlinear functions on the Gaussian space. Derivative, Sobolev spaces are introduced, while the famous Poincar inequality, logarithmic inequality, hypercontractive inequality, Meyer's inequality, Littlewood-Paley-Stein-Meyer theory are given in details.This book includes some basic material that cannot be found elsewhere that the author believes should be an integral part of the subject. For example, the book includes some interesting and important inequalities, the Littlewood-Paley-Stein-Meyer theory, and the H rmander theorem. The book also includes some recent progress achieved by the author and collaborators on density convergence, numerical solutions, local times.
Автор: Jamie D. Riggs Название: Handbook for Applied Modeling: Non-Gaussian and Correlated Data ISBN: 1316601056 ISBN-13(EAN): 9781316601051 Издательство: Cambridge Academ Рейтинг: Цена: 6019.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Designed for the applied practitioner, this book is a compact, entry-level guide to modeling and analyzing data that fail idealized assumptions. It explains and demonstrates core techniques, common pitfalls and data issues, and interpretation of model results, all with a focus on application, utility, and real-life data.
Автор: Merlevede, Florence (professor, Universite Paris-est Marne-la-vallee) Peligrad, Magda (professor, University Of Cincinnati) Utev, Sergey (university O Название: Functional gaussian approximation for dependent structures ISBN: 019882694X ISBN-13(EAN): 9780198826941 Издательство: Oxford Academ Рейтинг: Цена: 17820.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book has its origin in the need of developing and analysing mathematical models for phenomena that evolve in time and influence each another, and aims at a better understanding of the structure and asymptotic behaviour of stochastic processes.
Автор: Mandrekar Название: Stochastic Analysis For Gaussian Ra ISBN: 1498707815 ISBN-13(EAN): 9781498707817 Издательство: Taylor&Francis Рейтинг: Цена: 15312.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Stochastic Analysis for Gaussian Random Processes and Fields: With Applications presents Hilbert space methods to study deep analytic properties connecting probabilistic notions. In particular, it studies Gaussian random fields using reproducing kernel Hilbert spaces (RKHSs).
The book begins with preliminary results on covariance and associated RKHS before introducing the Gaussian process and Gaussian random fields. The authors use chaos expansion to define the Skorokhod integral, which generalizes the It integral. They show how the Skorokhod integral is a dual operator of Skorokhod differentiation and the divergence operator of Malliavin. The authors also present Gaussian processes indexed by real numbers and obtain a Kallianpur-Striebel Bayes' formula for the filtering problem. After discussing the problem of equivalence and singularity of Gaussian random fields (including a generalization of the Girsanov theorem), the book concludes with the Markov property of Gaussian random fields indexed by measures and generalized Gaussian random fields indexed by Schwartz space. The Markov property for generalized random fields is connected to the Markov process generated by a Dirichlet form.
Автор: Liu, Liguang Xiao, Jie Yang, Dachun Yuan, Wenping Название: Gaussian capacity analysis ISBN: 3319950398 ISBN-13(EAN): 9783319950396 Издательство: Springer Рейтинг: Цена: 6288.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This monograph develops the Gaussian functional capacity theory with applications to restricting the Gaussian Campanato/Sobolev/BV space. Included in the text is a new geometric characterization of the Gaussian 1-capacity and the Gaussian Poincar? 1-inequality. Applications to function spaces and geometric measures are also presented.This book will be of use to researchers who specialize in potential theory, elliptic differential equations, functional analysis, probability, and geometric measure theory.
Автор: Mandrekar, Vidyadhar S. Название: Stochastic Analysis for Gaussian Random Processes and Fields ISBN: 0367738147 ISBN-13(EAN): 9780367738143 Издательство: Taylor&Francis Рейтинг: Цена: 7348.00 р. Наличие на складе: Поставка под заказ.
Автор: Shaked, Moshe Название: Stable Non-Gaussian Random Processes ISBN: 0412051710 ISBN-13(EAN): 9780412051715 Издательство: Taylor&Francis Рейтинг: Цена: 29093.00 р. Наличие на складе: Поставка под заказ.
Описание: This handbook brings together a comprehensive collection of mathematical material in one location. It also offers a variety of new results interpreted in a form that is particularly useful to engineers, scientists, and applied mathematicians.
Автор: Franck Barthe, Pawel Wolff Название: Positive Gaussian Kernels Also Have Gaussian Minimizers ISBN: 1470451433 ISBN-13(EAN): 9781470451431 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 10659.00 р. Наличие на складе: Нет в наличии.
Описание: We study lower bounds on multilinear operators with Gaussian kernels acting on Lebesgue spaces, with exponents below one. We put forward natural conditions when the optimal constant can be computed by inspecting centered Gaussian functions only, and wegive necessary and sufficient conditions for this constant to be positive. Our work provides a counterpart to Lieb's results on maximizers of multilinear operators with real Gaussian kernels, also known as the multidimensional Brascamp-Lieb inequality. It unifies and extends severalinverse inequalities.
Автор: Marcus Название: Markov Processes, Gaussian Processes, and Local Times ISBN: 1107403758 ISBN-13(EAN): 9781107403758 Издательство: Cambridge Academ Рейтинг: Цена: 12038.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Two foremost researchers present important advances in stochastic process theory by linking well-understood (Gaussian) and less well-understood (Markov) classes of processes. It builds to this material through `mini-courses` on the relevant ingredients, which assume only measure-theoretic probability. This original, readable 2006 book is for researchers and advanced graduate students.
