Reproducing Kernel Hilbert Spaces in Probability and Statistics, Alain Berlinet; Christine Thomas-Agnan
Автор: Berlinet Alain, Thomas-Agnan Christine Название: Reproducing Kernel Hilbert Spaces in Probability and Statistics ISBN: 1402076797 ISBN-13(EAN): 9781402076794 Издательство: Springer Рейтинг: Цена: 23099 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book covers theoretical questions including the latest extension of the formalism (therefore of interest to pure mathematicians), as well as more practical ones such as computational issues. It focuses on some of the more fruitful and promising applications, including statistical signal processing, nonparametric curve estimation, random measures, limit theorems, learning theory and some applications at the fringe between Statistics and Approximation Theory. The intention is to put together topics apparently different but sharing the same background. The text is geared to graduate students in Statistics, Mathematics or Engineering, or to scientists with an equivalent level. A lot of examples and applications are given and the book contains a broad variety of exercises so that it can be used as a textbook at a postgraduate level.
Описание: Second order linear parabolic and elliptic equations arise frequently in mathematics and other disciplines. For example parabolic equations are to be found in statistical mechanics and solid state theory, their infinite dimensional counterparts are important in fluid mechanics, mathematical finance and population biology, whereas nonlinear parabolic equations arise in control theory. Here the authors present a state of the art treatment of the subject from a new perspective. The main tools used are probability measures in Hilbert and Banach spaces and stochastic evolution equations. There is then a discussion of how the results in the book can be applied to control theory. This area is developing very rapidly and there are numerous notes and references that point the reader to more specialised results not covered in the book. Coverage of some essential background material will help make the book self-contained and increase its appeal to those entering the subject.
Описание: The Hilbert-Huang Transform ((HHT) is a recently developed technique which is used to analyze nonstationary data. Hydrologic and environmental series are, in the main, analyzed by using techniques which were developed for stationary data. This has led to problems of interpretation of the results. Environmental and hydrologic series are quite often nonstationary. The basic objective of the material discussed in this book is to analyze these data by using methods based on the Hilbert-Huang transform. These results are compared to the results from the traditional methods such as those based on Fourier transform and other classical statistical tests.
Описание: This book provides an alternative approach to study the pre-kernel solution of transferable utility games based on a generalized conjugation theory from convex analysis.
Автор: Masayuki Hirukawa; Mari Sakudo Название: Asymmetric Kernel Smoothing ISBN: 9811054657 ISBN-13(EAN): 9789811054655 Издательство: Springer Рейтинг: Цена: 5774 р. Наличие на складе: Поставка под заказ.
Описание: Lastly, the book addresses the applications of asymmetric kernel estimation and testing to various forms of nonnegative economic and financial data. Until recently, the most popularly chosen nonparametric methods used symmetric kernel functions to estimate probability density functions of symmetric distributions with unbounded support.
Описание: Methods of kernel estimates represent one of the most effective nonparametric smoothing techniques. These methods are simple to understand and they possess very good statistical properties. This book provides a concise and comprehensive overview of statistical theory and in addition, emphasis is given to the implementation of presented methods in Matlab. All created programs are included in a special toolbox which is an integral part of the book. This toolbox contains many Matlab scripts useful for kernel smoothing of density, cumulative distribution function, regression function, hazard function, indices of quality and bivariate density. Specifically, methods for choosing a choice of the optimal bandwidth and a special procedure for simultaneous choice of the bandwidth, the kernel and its order are implemented. The toolbox is divided into six parts according to the chapters of the book.All scripts are included in a user interface and it is easy to manipulate with this interface. Each chapter of the book contains a detailed help for the related part of the toolbox too. This book is intended for newcomers to the field of smoothing techniques and would also be appropriate for a wide audience: advanced graduate, PhD students and researchers from both the statistical science and interface disciplines.
Автор: Davier Название: The Kernel Method of Test Equating ISBN: 0387019855 ISBN-13(EAN): 9780387019857 Издательство: Springer Рейтинг: Цена: 19634 р. Наличие на складе: Поставка под заказ.
Описание: Kernel Equating (KE) is a modern and unified approach to test equating. This book applies KE to the four major equating designs and to both Chain Equating and Post-Stratification Equating for the Non-Equivalent groups with Anchor Test Design.
Описание: This book provides an alternative approach to study the pre-kernel solution of transferable utility games based on a generalized conjugation theory from convex analysis.
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