Functional and High-Dimensional Statistics and Related Fields, Aneiros Germбn, Horovб Ivana, Huskovб Marie

Название: Functional statistics and related fields.
ISBN: 3319558455 ISBN-13(EAN): 9783319558455
Издательство: Springer
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Цена: 121110.00 T
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Описание: This volume collects latest methodological and applied contributions on functional, high-dimensional and other complex data, related statistical models and tools as well as on operator-based statistics.

Автор: Karl K. Sabelfeld, Nikolai A. Simonov
Название: Stochastic Methods for Boundary Value Problems: Numerics for High-dimensional PDEs and Applications
ISBN: 3110479060 ISBN-13(EAN): 9783110479065
Издательство: Walter de Gruyter
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Цена: 123910.00 T
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Описание: This monograph is devoted to random walk based stochastic algorithms for solving high-dimensional boundary value problems of mathematical physics and chemistry. It includes Monte Carlo methods where the random walks live not only on the boundary, but also inside the domain. A variety of examples from capacitance calculations to electron dynamics in semiconductors are discussed to illustrate the viability of the approach.The book is written for mathematicians who work in the field of partial differential and integral equations, physicists and engineers dealing with computational methods and applied probability, for students and postgraduates studying mathematical physics and numerical mathematics. Contents: IntroductionRandom walk algorithms for solving integral equationsRandom walk-on-boundary algorithms for the Laplace equationWalk-on-boundary algorithms for the heat equationSpatial problems of elasticityVariants of the random walk on boundary for solving stationary potential problemsSplitting and survival probabilities in random walk methods and applicationsA random WOS-based KMC method for electron-hole recombinationsMonte Carlo methods for computing macromolecules properties and solving related problemsBibliography

Автор: Koch
Название: Analysis of Multivariate and High-Dimensional Data
ISBN: 0521887933 ISBN-13(EAN): 9780521887939
Издательство: Cambridge Academ
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Цена: 70750.00 T
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Описание: `Big data` poses challenges that require both classical multivariate methods and modern machine-learning techniques. This coherent treatment integrates theory with data analysis, visualisation and interpretation of the analysis. Problems, data sets and MATLAB (R) code complete the package. It is suitable for master`s/graduate students in statistics and working scientists in data-rich disciplines.

Автор: Peter B?hlmann; Sara van de Geer
Название: Statistics for High-Dimensional Data
ISBN: 3642268579 ISBN-13(EAN): 9783642268571
Издательство: Springer
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Цена: 111790.00 T
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Описание: This valuable compendium of statistical methods features a unique combination of methodology, theory, algorithms and applications. It covers recently developed approaches to handling large and complex data sets, including the Lasso and boosting methods.

Автор: Giraud
Название: Introduction to High-Dimensional Statistics
ISBN: 1482237946 ISBN-13(EAN): 9781482237948
Издательство: Taylor&Francis
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Цена: 64300.00 T
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Описание: Ever-greater computing technologies have given rise to an exponentially growing volume of data. Today massive data sets (with potentially thousands of variables) play an important role in almost every branch of modern human activity, including networks, finance, and genetics. However, analyzing such data has presented a challenge for statisticians and data analysts and has required the development of new statistical methods capable of separating the signal from the noise. Introduction to High-Dimensional Statistics is a concise guide to state-of-the-art models, techniques, and approaches for handling high-dimensional data. The book is intended to expose the reader to the key concepts and ideas in the most simple settings possible while avoiding unnecessary technicalities. Offering a succinct presentation of the mathematical foundations of high-dimensional statistics, this highly accessible text: Describes the challenges related to the analysis of high-dimensional data Covers cutting-edge statistical methods including model selection, sparsity and the lasso, aggregation, and learning theory Provides detailed exercises at the end of every chapter with collaborative solutions on a wikisite Illustrates concepts with simple but clear practical examples Introduction to High-Dimensional Statistics is suitable for graduate students and researchers interested in discovering modern statistics for massive data. It can be used as a graduate text or for self-study.

Автор: Pons, Odile,
Название: Orthonormal series estimators /
ISBN: 9811210683 ISBN-13(EAN): 9789811210686
Издательство: World Scientific Publishing
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Цена: 95040.00 T
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Описание: The approximation and the estimation of nonparametric functions by projections on an orthonormal basis of functions are useful in data analysis. This book presents series estimators defined by projections on bases of functions, they extend the estimators of densities to mixture models, deconvolution and inverse problems, to semi-parametric and nonparametric models for regressions, hazard functions and diffusions. They are estimated in the Hilbert spaces with respect to the distribution function of the regressors and their optimal rates of convergence are proved. Their mean square errors depend on the size of the basis which is consistently estimated by cross-validation. Wavelets estimators are defined and studied in the same models.The choice of the basis, with suitable parametrizations, and their estimation improve the existing methods and leads to applications to a wide class of models. The rates of convergence of the series estimators are the best among all nonparametric estimators with a great improvement in multidimensional models. Original methods are developed for the estimation in deconvolution and inverse problems. The asymptotic properties of test statistics based on the estimators are also established.

Автор: Gin?
Название: Mathematical Foundations of Infinite-Dimensional Statistical Models
ISBN: 1107043166 ISBN-13(EAN): 9781107043169
Издательство: Cambridge Academ
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Цена: 99270.00 T
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Описание: High-dimensional and nonparametric statistical models are ubiquitous in modern data science. This book develops a mathematically coherent and objective approach to statistical inference in such models, with a focus on function estimation problems arising from random samples (density estimation) or from Gaussian regression/signal in white noise problems.

Автор: Kythe
Название: Elements Of Concave Analysis And Applications
ISBN: 1138705284 ISBN-13(EAN): 9781138705289
Издательство: Taylor&Francis
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Цена: 163330.00 T
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Описание: The aim of Elements of Concave Analysis and Applications is to provide a basic and self-contained introduction to concepts and detailed study of concave and convex functions. It is written in the style of a textbook, designed for courses in mathematical economics, finance, and manufacturing design.

Автор: Yoichi Oshima
Название: Semi-Dirichlet Forms and Markov Processes
ISBN: 3110302004 ISBN-13(EAN): 9783110302004
Издательство: Walter de Gruyter
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Цена: 123910.00 T
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Описание: Thisbook deals with analytic treatments of Markov processes. Symmetric Dirichlet forms andtheir associated Markov processes are important and powerful toolsin the theory of Markovprocesses and their applications. The theoryis well studied and used in various fields. In this monograph, we intend togeneralize the theory to non-symmetric and time dependent semi-Dirichlet forms. By this generalization, we can cover the wide class of Markov processes and analytic theory which do not possess the dualMarkov processes. In particular, under the semi-Dirichlet form setting, the stochastic calculus is not well established yet.In this monograph, we intend to give an introduction to such calculus. Furthermore, basic examples different from the symmetric cases are given.Thetext is writtenfor graduate students, but alsoresearchers.

Автор: B?hlmann
Название: Statistics for High Dimensional Data
ISBN: 3642201911 ISBN-13(EAN): 9783642201912
Издательство: Springer
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Цена: 111790.00 T
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Описание: This valuable compendium of statistical methods features a unique combination of methodology, theory, algorithms and applications. It covers recently developed approaches to handling large and complex data sets, including the Lasso and boosting methods.

Автор: Sergey Bobkov, Michel Ledoux
Название: One-Dimensional Empirical Measures, Order Statistics, and Kantorovich Transport Distances
ISBN: 1470436507 ISBN-13(EAN): 9781470436506
Издательство: Mare Nostrum (Eurospan)
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Цена: 67710.00 T
Наличие на складе: Невозможна поставка.
Описание: This work is devoted to the study of rates of convergence of the empirical measures $\mu_{n} = \frac {1}{n} \sum_{k=1}^n \delta_{X_k}$, $n \geq 1$, over a sample $(X_{k})_{k \geq 1}$ of independent identically distributed real-valued random variables towards the common distribution $\mu$ in Kantorovich transport distances $W_p$. The focus is on finite range bounds on the expected Kantorovich distances $\mathbb{E}(W_{p}(\mu_{n},\mu ))$ or $\big [ \mathbb{E}(W_{p}^p(\mu_{n},\mu )) \big ]^1/p$ in terms of moments and analytic conditions on the measure $\mu $ and its distribution function. The study describes a variety of rates, from the standard one $\frac {1}{\sqrt n}$ to slower rates, and both lower and upper-bounds on $\mathbb{E}(W_{p}(\mu_{n},\mu ))$ for fixed $n$ in various instances. Order statistics, reduction to uniform samples and analysis of beta distributions, inverse distribution functions, log-concavity are main tools in the investigation. Two detailed appendices collect classical and some new facts on inverse distribution functions and beta distributions and their densities necessary to the investigation.

Автор: Bai Zhidong
Название: Spectral Theory of Large Dimensional Random Matrices and its
ISBN: 981457905X ISBN-13(EAN): 9789814579056
Издательство: World Scientific Publishing
Цена: 85530.00 T
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Описание: The book contains three parts: Spectral theory of large dimensional random matrices; Applications to wireless communications; and Applications to finance. In the first part, we introduce some basic theorems of spectral analysis of large dimensional random matrices that are obtained under finite moment conditions, such as the limiting spectral distributions of Wigner matrix and that of large dimensional sample covariance matrix, limits of extreme eigenvalues, and the central limit theorems for linear spectral statistics. In the second part, we introduce some basic examples of applications of random matrix theory to wireless communications and in the third part, we present some examples of Applications to statistical finance.