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Matrices, Statistics and Big Data, S. Ejaz Ahmed; Francisco Carvalho; Simo Puntanen


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Автор: S. Ejaz Ahmed; Francisco Carvalho; Simo Puntanen
Название:  Matrices, Statistics and Big Data
ISBN: 9783030175184
Издательство: Springer
Классификация:





ISBN-10: 3030175189
Обложка/Формат: Hardcover
Страницы: 190
Вес: 0.48 кг.
Дата издания: 2019
Серия: Contributions to Statistics
Язык: English
Издание: 1st ed. 2019
Иллюстрации: 14 illustrations, color; 10 illustrations, black and white; xii, 190 p. 24 illus., 14 illus. in color.
Размер: 234 x 156 x 13
Читательская аудитория: Professional & vocational
Основная тема: Statistics
Подзаголовок: Selected Contributions from IWMS 2016
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This volume features selected, refereed papers on various aspects of statistics, matrix theory and its applications to statistics, as well as related numerical linear algebra topics and numerical solution methods, which are relevant for problems arising in statistics and in big data. The contributions were originally presented at the 25th International Workshop on Matrices and Statistics (IWMS 2016), held in Funchal (Madeira), Portugal on June 6-9, 2016. The IWMS workshop series brings together statisticians, computer scientists, data scientists and mathematicians, helping them better understand each other’s tools, and fostering new collaborations at the interface of matrix theory and statistics.
Дополнительное описание: Preface (S. Ejaz Ahmed, Francisco Carvalho, Simo Puntanen).- Further properties of the linear sufficiency in the partitioned linear model (Augustyn Markiewicz, Simo Puntanen).- Hybrid model for recurrent event data (Ivo Sousa-Ferreira, Ana Maria Abreu).-



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.

Log-Gases and Random Matrices

Автор: Forrester Peter J
Название: Log-Gases and Random Matrices
ISBN: 0691128294 ISBN-13(EAN): 9780691128290
Издательство: Wiley
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Цена: 20592.00 р.
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Описание: Random matrix theory, both as an application and as a theory, has evolved rapidly over the years. This title chronicles these developments, emphasizing log-gases as a physical picture. It covers topics such as beta ensembles and Jack polynomials. It develops the application and theory of Gaussian and circular ensembles of random matrix theory.

Multivariate Statistics: Theory And Applications - Proceedings Of The Ix Tartu Conference On Multivariate Statistics And Xx International Workshop On Matrices And Statistics

Автор: Kollo Tonu
Название: Multivariate Statistics: Theory And Applications - Proceedings Of The Ix Tartu Conference On Multivariate Statistics And Xx International Workshop On Matrices And Statistics
ISBN: 9814449393 ISBN-13(EAN): 9789814449397
Издательство: World Scientific Publishing
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Цена: 16790.00 р.
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Описание: The book aims to present a wide range of the newest results on multivariate statistical models, distribution theory and applications of multivariate statistical methods. A paper on Pearson-Kotz-Dirichlet distributions by Professor N Balakrishnan contains main results of the Samuel Kotz Memorial Lecture. Extensions of linear models to multivariate exponential dispersion models and Growth Curve models are presented, and several papers on classification methods are included. Applications range from insurance mathematics to medical and industrial statistics and sampling algorithms.

Linear Models And Regression With R: An Integrated Approach

Автор: Jammalamadaka S Rao, Sengupta Debasis
Название: Linear Models And Regression With R: An Integrated Approach
ISBN: 9811200408 ISBN-13(EAN): 9789811200403
Издательство: World Scientific Publishing
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Цена: от 6763.00 р.
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Описание:

Starting with the basic linear model where the design and covariance matrices are of full rank, this book demonstrates how the same statistical ideas can be used to explore the more general linear model with rank-deficient design and/or covariance matrices. The unified treatment presented here provides a clearer understanding of the general linear model from a statistical perspective, thus avoiding the complex matrix-algebraic arguments that are often used in the rank-deficient case. Elegant geometric arguments are used as needed.

The book has a very broad coverage, from illustrative practical examples in Regression and Analysis of Variance alongside their implementation using R, to providing comprehensive theory of the general linear model with 181 worked-out examples, 227 exercises with solutions, 152 exercises without solutions (so that they may be used as assignments in a course), and 320 up-to-date references.

This completely updated and new edition of Linear Models: An Integrated Approach includes the following features:

  • Applications with data sets, and their implementation in R,
  • Comprehensive coverage of regression diagnostics and model building,
  • Coverage of other special topics such as collinearity, stochastic and inequality constraints, misspecified models, etc.,
  • Use of simple statistical ideas and interpretations to explain advanced concepts, and simpler proofs of many known results,
  • Discussion of models covering mixed-effects/variance components, spatial, and time series data with partially unknown dispersion matrix,
  • Thorough treatment of the singular linear model, including the case of multivariate response,
  • Insight into updates in the linear model, and their connection with diagnostics, design, variable selection, Kalman filter, etc.,
  • Extensive discussion of the foundations of linear inference, along with linear alternatives to least squares.
Random matrices: high dimensional phenomena

Автор: Blower, Gordon
Название: Random matrices: high dimensional phenomena
ISBN: 0521133122 ISBN-13(EAN): 9780521133128
Издательство: Cambridge Academ
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Цена: 10138.00 р.
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Описание: An introduction to the behaviour of random matrices. Suitable for postgraduate students and non-experts.

Random Matrices,142

Автор: Madan Lal Mehta
Название: Random Matrices,142
ISBN: 0120884097 ISBN-13(EAN): 9780120884094
Издательство: Elsevier Science
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Цена: 19370.00 р.
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Описание: Gives a description of analytical methods devised to study random matrices. This work reflects the developments in the field. It includes a coverage of skew-orthogonal and bi-orthogonal polynomials and their use in the evaluation of some multiple integrals. It also presents Fredholm determinants and Painleve equations.

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.

Introduction to random matrices

Автор: Anderson, Greg W. Guionnet, Alice Zeitouni, Ofer
Название: Introduction to random matrices
ISBN: 0521194520 ISBN-13(EAN): 9780521194525
Издательство: Cambridge Academ
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Цена: 11088.00 р.
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Описание: The theory of random matrices plays an important role in many areas of pure mathematics. This rigorous introduction is specifically designed for graduate students in mathematics or related sciences, who have a background in probability theory but have not been exposed to advanced notions of functional analysis, algebra or geometry.

Spectral Theory of Large Dimensional Random Matrices and its

Автор: Bai Zhidong
Название: Spectral Theory of Large Dimensional Random Matrices and its
ISBN: 981457905X ISBN-13(EAN): 9789814579056
Издательство: World Scientific Publishing
Цена: 12830.00 р.
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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.

Random Matrices And Random Partitions: Normal Convergence

Автор: Su Zhonggen
Название: Random Matrices And Random Partitions: Normal Convergence
ISBN: 9814612227 ISBN-13(EAN): 9789814612227
Издательство: World Scientific Publishing
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Цена: 13939.00 р.
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Описание: This Book Is Aimed At Graduate Students And Researchers Who Are Interested In The Probability Limit Theory Of Random Matrices And Random Partitions. It Mainly Consists Of Three Parts. Part I Is A Brief Review Of Classical Central Limit Theorems For Sums Of Independent Random Variables, Martingale Sequences And Markov Chains, Etc. These Classical Theorems Are Frequently Used In The Study Of Random Matrices And Random Partitions Where Random Matrices Are Well-Studied In Probability Theory. Part Ii Concentrates On The Asymptotic Distribution Theory Of Circular Unitary Ensemble And Gaussian Unitary Ensemble, Which Are Prototypes Of Random Matrix Theory. It Turns Out That The Classical Central Limit Theorems And Methods Are Applicable In Describing Asymptotic Distributions Of Eigenvalue Statistics Like Linear Functionals Of Eigenvalues. This Is Attributed To The Nice Algebraic Structures Of Models. This Part Also Studies The Circular β Ensembles And Gaussian β Ensembles, Which May Be Viewed As Extensions Of The Circular Unitary Ensemble And Gaussian Unitary Ensemble. Part Iii Is Devoted To The Study Of Random Uniform And Plancherel Partitions. As Is Known, There Is A Surprising Similarity Between Random Matrices And Random Integer Partitions From The Viewpoint Of Asymptotic Distribution Theory, Though It Is Difficult To Find Any Direct Link Between The Two Finite Models.This Book Treats Only Second-Order Fluctuations For Primary Random Variables From Two Classes Of Special Random Models. It Is Written In A Clear, Concise And Pedagogical Way. It May Be Read As An Introductory Text To Further Study Probability Theory Of General Random Matrices, Random Partitions And Even Random Point Processes. This Book Is Aimed At Graduate Students And Researchers Who Are Interested In Probability Limit Theory Of Random Matrices And Random Integer Partitions.


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