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Functional statistics and related fields., 


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Название:  Functional statistics and related fields.
ISBN: 9783319558455
Издательство: Springer
Классификация:


ISBN-10: 3319558455
Обложка/Формат: Paperback
Страницы: 288
Вес: 0.48 кг.
Дата издания: 28.04.2017
Серия: Contributions to statistics
Язык: English
Издание: 1st ed. 2017
Иллюстрации: 40 illustrations, black and white; xxiv, 288 p. 40 illus.
Размер: 234 x 156 x 17
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
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Поставляется из: Германии
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.


Counterfactuals and Causal Inference

Автор: Morgan
Название: Counterfactuals and Causal Inference
ISBN: 1107694167 ISBN-13(EAN): 9781107694163
Издательство: Cambridge Academ
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Цена: 5702.00 р.
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Описание: Cause-and-effect questions are the motivation for most research in the social, demographic, and health sciences. The counterfactual approach to causal analysis represents a unified framework for the prosecution of these questions. This second edition aims to convince more social scientists to take this approach when analyzing these core empirical questions.

Analysis on Gaussian Spaces

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.

Introduction to Probability, Second Edition

Автор: Joseph K. Blitzstein, Jessica Hwang
Название: Introduction to Probability, Second Edition
ISBN: 1138369918 ISBN-13(EAN): 9781138369917
Издательство: Taylor&Francis
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Цена: 11176.00 р.
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Описание: Assumes one-semester of calculus. "Stories" make distributions (Normal, Binomial, Poisson that are widely-used in statistics) easier to remember, understand. Many books write down formulas without explaining clearly why these particular distributions are important or how they are all connected.

Matrix Differential Calculus with Applications in Statistics and Econometrics

Автор: Jan R. Magnus, Heinz Neudecker
Название: Matrix Differential Calculus with Applications in Statistics and Econometrics
ISBN: 1119541204 ISBN-13(EAN): 9781119541202
Издательство: Wiley
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Цена: 14090.00 р.
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Описание:

A brand new, fully updated edition of a popular classic on matrix differential calculus with applications in statistics and econometrics

This exhaustive, self-contained book on matrix theory and matrix differential calculus provides a treatment of matrix calculus based on differentials and shows how easy it is to use this theory once you have mastered the technique. Jan Magnus, who, along with the late Heinz Neudecker, pioneered the theory, develops it further in this new edition and provides many examples along the way to support it.

Matrix calculus has become an essential tool for quantitative methods in a large number of applications, ranging from social and behavioral sciences to econometrics. It is still relevant and used today in a wide range of subjects such as the biosciences and psychology. Matrix Differential Calculus with Applications in Statistics and Econometrics, Third Edition contains all of the essentials of multivariable calculus with an emphasis on the use of differentials. It starts by presenting a concise, yet thorough overview of matrix algebra, then goes on to develop the theory of differentials. The rest of the text combines the theory and application of matrix differential calculus, providing the practitioner and researcher with both a quick review and a detailed reference.

  • Fulfills the need for an updated and unified treatment of matrix differential calculus
  • Contains many new examples and exercises based on questions asked of the author over the years
  • Covers new developments in field and features new applications
  • Written by a leading expert and pioneer of the theory
  • Part of the Wiley Series in Probability and Statistics

Matrix Differential Calculus With Applications in Statistics and Econometrics Third Edition is an ideal text for graduate students and academics studying the subject, as well as for postgraduates and specialists working in biosciences and psychology.

Functional and High-Dimensional Statistics and Related Fields

Автор: Aneiros Germбn, Horovб Ivana, Huskovб Marie
Название: Functional and High-Dimensional Statistics and Related Fields
ISBN: 303047755X ISBN-13(EAN): 9783030477554
Издательство: Springer
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Цена: 20962.00 р.
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Описание: Preface.- List of Contributors .- 1 An introduction to the (postponed) 5th edition of the International Workshop on Functional and Operatorial Statistics.- 2 Analysis of Telecom Italia Mobile Phone Data by Space-time Regression with Differential Regularization.- 3 Some Numerical Test on the Convergence Rates of Regression with Differential Regularization.- 4 Learning with Signatures.- 5 About the Complexity Function in Small-ball Probability Factorization.- 6 Principal Components Analysis of a Cyclostationary Random Function.- 7 Level Set and Density Estimation on Manifolds.- 8 Pseudo-metrics as Interesting Tool in Nonparametric Functional Regression.- 9 Testing a Specification Form in Single Functional Index Model.- 10 A New Method for Ordering Functional Data and its Application to Diagnostic Test.- 11 A Functional Data Analysis Approach to the Estimation of Densities over Complex Regions.- 12 A Conformal Approach for Distribution-free Prediction of Functional Data.- 13 G-Lasso Network Analysis for Functional Data.- 14 Modelling Functional Data with High-dimensional Error Structure.- 15 Goodness-of-fit Tests for Functional Linear Models Based on Integrated Projections.- 16 From High-dimensional to Functional Data: Stringing Via Manifold Learning.- 17 Functional Two-sample Tests Based on Empirical Characteristic Functionals.- 18 Some Remarks on the Nelson-Siegel Model.- 19 Modeling the Effect of Recurrent Events on Time-to-event Processes by Means of Functional Data.- 20 On Robust Training of Regression Neural Networks.- 21 Simultaneous Inference for Function-valued Parameters: a Fast and Fair Approach.- 22 Single Functional Index Model under Responses MAR and Dependent Observations.- 23 O2S2 for the Geodata Deluge .- 24 Riemannian Distances between Covariance Operators and Gaussian Processes.- 25 Depth in Infinite-dimensional Spaces.- 26 Variable Selection in Semiparametric Bi-functional Models.- 27 Local Inference for Functional Data Controlling the Functional False Discovery Rate.- 28 Optimum Scale Selection for 3D Point Cloud Classification through Distance Correlation.- 29 Generalized Functional Partially Linear Single-index Models.- 30 Functional Outlier Detection through Probabilistic Modelling.- 31 Topological Object Data Analysis Methods with an Application to Medical Imaging .- 32 Distribution-free Pointwise Adjusted %-values for Functional Hypotheses.- Authors Index.

Orthonormal series estimators /

Автор: Pons, Odile,
Название: Orthonormal series estimators /
ISBN: 9811210683 ISBN-13(EAN): 9789811210686
Издательство: World Scientific Publishing
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Цена: 14256.00 р.
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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.

Convergence of One-Parameter Operator Semigroups

Автор: Bobrowski
Название: Convergence of One-Parameter Operator Semigroups
ISBN: 1107137438 ISBN-13(EAN): 9781107137431
Издательство: Cambridge Academ
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Цена: 23285.00 р.
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Описание: Written by a leading expert in the field, this book presents the classical theory of convergence of semigroups and then uses real examples to show how it can be applied to models of mathematical biology as well as other branches of mathematics.

Probability and Statistics for Engineering and the Sciences

Автор: Devore Jay L.
Название: Probability and Statistics for Engineering and the Sciences
ISBN: 1337094269 ISBN-13(EAN): 9781337094269
Издательство: Cengage Learning
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Цена: 10770.00 р.
Наличие на складе: Нет в наличии.

Описание: Put statistical theories into practice with PROBABILITY AND STATISTICS FOR ENGINEERING AND THE SCIENCES, 9E, INTERNATIONAL METRIC EDITION. Always a market favorite, this calculus-based book offers a comprehensive introduction to probability and statistics while demonstrating how to apply concepts, models, and methodologies in today's engineering and scientific workplaces. Jay Devore, an award-winning professor and internationally recognized author and statistician, stresses lively examples and engineering activities to drive home the numbers without exhaustive mathematical development and derivations.

Many examples, practice problems, sample tests, and simulations based on real data and issues help you build a more intuitive connection to the material. A proven and accurate book, PROBABILITY AND STATISTICS FOR ENGINEERING AND THE SCIENCES, 9E, INTERNATIONAL METRIC EDITION also includes graphics and screen shots from SAS (R), MINITAB (R), and Java (TM) Applets to give you a solid perspective of statistics in action.

Martingales in Banach Spaces

Автор: Pisier
Название: Martingales in Banach Spaces
ISBN: 1107137241 ISBN-13(EAN): 9781107137240
Издательство: Cambridge Academ
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Цена: 9979.00 р.
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Описание: Martingales arise in many areas of probability theory. This book focuses on their applications to the geometry of Banach spaces and discusses the interplay of Banach space valued martingales with various other areas of analysis. It is accessible to graduates with a basic knowledge of real and complex analysis.

Probabilistic Normed Spaces

Автор: Guillen Bernardo Lafuerza, Harikrishnan Panackal
Название: Probabilistic Normed Spaces
ISBN: 1783264683 ISBN-13(EAN): 9781783264681
Издательство: World Scientific Publishing
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Цена: 11563.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book provides a comprehensive foundation in Probabilistic Normed (PN) Spaces for anyone conducting research in this field of mathematics and statistics.

Functional and High-Dimensional Statistics and Related Fields

Автор: Aneiros Germбn, Horovб Ivana, Huskovб Marie
Название: Functional and High-Dimensional Statistics and Related Fields
ISBN: 3030477584 ISBN-13(EAN): 9783030477585
Издательство: Springer
Цена: 20962.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Preface.- List of Contributors .- 1 An introduction to the (postponed) 5th edition of the International Workshop on Functional and Operatorial Statistics.- 2 Analysis of Telecom Italia Mobile Phone Data by Space-time Regression with Differential Regularization.- 3 Some Numerical Test on the Convergence Rates of Regression with Differential Regularization.- 4 Learning with Signatures.- 5 About the Complexity Function in Small-ball Probability Factorization.- 6 Principal Components Analysis of a Cyclostationary Random Function.- 7 Level Set and Density Estimation on Manifolds.- 8 Pseudo-metrics as Interesting Tool in Nonparametric Functional Regression.- 9 Testing a Specification Form in Single Functional Index Model.- 10 A New Method for Ordering Functional Data and its Application to Diagnostic Test.- 11 A Functional Data Analysis Approach to the Estimation of Densities over Complex Regions.- 12 A Conformal Approach for Distribution-free Prediction of Functional Data.- 13 G-Lasso Network Analysis for Functional Data.- 14 Modelling Functional Data with High-dimensional Error Structure.- 15 Goodness-of-fit Tests for Functional Linear Models Based on Integrated Projections.- 16 From High-dimensional to Functional Data: Stringing Via Manifold Learning.- 17 Functional Two-sample Tests Based on Empirical Characteristic Functionals.- 18 Some Remarks on the Nelson-Siegel Model.- 19 Modeling the Effect of Recurrent Events on Time-to-event Processes by Means of Functional Data.- 20 On Robust Training of Regression Neural Networks.- 21 Simultaneous Inference for Function-valued Parameters: a Fast and Fair Approach.- 22 Single Functional Index Model under Responses MAR and Dependent Observations.- 23 O2S2 for the Geodata Deluge .- 24 Riemannian Distances between Covariance Operators and Gaussian Processes.- 25 Depth in Infinite-dimensional Spaces.- 26 Variable Selection in Semiparametric Bi-functional Models.- 27 Local Inference for Functional Data Controlling the Functional False Discovery Rate.- 28 Optimum Scale Selection for 3D Point Cloud Classification through Distance Correlation.- 29 Generalized Functional Partially Linear Single-index Models.- 30 Functional Outlier Detection through Probabilistic Modelling.- 31 Topological Object Data Analysis Methods with an Application to Medical Imaging .- 32 Distribution-free Pointwise Adjusted %-values for Functional Hypotheses.- Authors Index.

Bayesian Data Analysis, Third Edition

Автор: Gelman
Название: Bayesian Data Analysis, Third Edition
ISBN: 1439840954 ISBN-13(EAN): 9781439840955
Издательство: Taylor&Francis
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Цена: 11088.00 р.
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Описание: Winner of the 2016 De Groot Prize from the International Society for Bayesian Analysis Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.


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