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Gaussian Measures in Hilbert Space

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Release : 2020-02-26
Genre : Mathematics
Kind : eBook
Book Rating : 675/5 ( reviews)

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Book Synopsis Gaussian Measures in Hilbert Space by : Alexander Kukush

Download or read book Gaussian Measures in Hilbert Space written by Alexander Kukush. This book was released on 2020-02-26. Available in PDF, EPUB and Kindle. Book excerpt: At the nexus of probability theory, geometry and statistics, a Gaussian measure is constructed on a Hilbert space in two ways: as a product measure and via a characteristic functional based on Minlos-Sazonov theorem. As such, it can be utilized for obtaining results for topological vector spaces. Gaussian Measures contains the proof for Ferniques theorem and its relation to exponential moments in Banach space. Furthermore, the fundamental Feldman-Hájek dichotomy for Gaussian measures in Hilbert space is investigated. Applications in statistics are also outlined. In addition to chapters devoted to measure theory, this book highlights problems related to Gaussian measures in Hilbert and Banach spaces. Borel probability measures are also addressed, with properties of characteristic functionals examined and a proof given based on the classical Banach–Steinhaus theorem. Gaussian Measures is suitable for graduate students, plus advanced undergraduate students in mathematics and statistics. It is also of interest to students in related fields from other disciplines. Results are presented as lemmas, theorems and corollaries, while all statements are proven. Each subsection ends with teaching problems, and a separate chapter contains detailed solutions to all the problems. With its student-tested approach, this book is a superb introduction to the theory of Gaussian measures on infinite-dimensional spaces.

Gaussian Measures in Banach Spaces

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Release : 2006-11-14
Genre : Mathematics
Kind : eBook
Book Rating : 082/5 ( reviews)

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Book Synopsis Gaussian Measures in Banach Spaces by : H.-H. Kuo

Download or read book Gaussian Measures in Banach Spaces written by H.-H. Kuo. This book was released on 2006-11-14. Available in PDF, EPUB and Kindle. Book excerpt:

Gaussian Measures

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Release : 2015-01-26
Genre : Mathematics
Kind : eBook
Book Rating : 69X/5 ( reviews)

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Book Synopsis Gaussian Measures by : Vladimir I. Bogachev

Download or read book Gaussian Measures written by Vladimir I. Bogachev. This book was released on 2015-01-26. Available in PDF, EPUB and Kindle. Book excerpt: This book gives a systematic exposition of the modern theory of Gaussian measures. It presents with complete and detailed proofs fundamental facts about finite and infinite dimensional Gaussian distributions. Covered topics include linear properties, convexity, linear and nonlinear transformations, and applications to Gaussian and diffusion processes. Suitable for use as a graduate text and/or a reference work, this volume contains many examples, exercises, and an extensive bibliography. It brings together many results that have not appeared previously in book form.

Analysis On Gaussian Spaces

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Release : 2016-08-30
Genre : Mathematics
Kind : eBook
Book Rating : 197/5 ( reviews)

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Book Synopsis Analysis On Gaussian Spaces by : Yaozhong Hu

Download or read book Analysis On Gaussian Spaces written by Yaozhong Hu. This book was released on 2016-08-30. Available in PDF, EPUB and Kindle. Book excerpt: '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 Poincaré 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 Hörmander theorem. The book also includes some recent progress achieved by the author and collaborators on density convergence, numerical solutions, local times.

Gaussian Hilbert Spaces

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Release : 1997-06-12
Genre : Mathematics
Kind : eBook
Book Rating : 280/5 ( reviews)

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Book Synopsis Gaussian Hilbert Spaces by : Svante Janson

Download or read book Gaussian Hilbert Spaces written by Svante Janson. This book was released on 1997-06-12. Available in PDF, EPUB and Kindle. Book excerpt: This book treats the very special and fundamental mathematical properties that hold for a family of Gaussian (or normal) random variables. Such random variables have many applications in probability theory, other parts of mathematics, statistics and theoretical physics. The emphasis throughout this book is on the mathematical structures common to all these applications. This will be an excellent resource for all researchers whose work involves random variables.

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