Large Covariance and Autocovariance Matrices, Bose, Arup
Автор: Pourahmadi Mohsen Название: High-dimensional Covariance Estimation ISBN: 1118034295 ISBN-13(EAN): 9781118034293 Издательство: Wiley Рейтинг: Цена: 12664.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Methods for estimating sparse and large covariance matrices Covariance and correlation matrices play fundamental roles in every aspect of the analysis of multivariate data collected from a variety of fields including business and economics, health care, engineering, and environmental and physical sciences.
Автор: Milliken Название: Analysis of Messy Data, Volume III ISBN: 158488083X ISBN-13(EAN): 9781584880837 Издательство: Taylor&Francis Рейтинг: Цена: 24499.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Analysis of covariance is a very useful but often misunderstood methodology for analyzing data where important characteristics of the experimental units are measured but not included as factors in the design. With a balance of theory and examples, this volume provides a guide to this strategy`s techniques, theory, and application.
Описание: This valuable reference on projectors, generalized inverses, and SVD covers concepts numerous cutting-edge concepts and provides systematic and in-depth accounts of these ideas from the viewpoint of linear transformations of finite dimensional vector spaces.
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 Рейтинг: Цена: от 6763.00 р. Наличие на складе: Есть
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.
Автор: Tsukuma Hisayuki, Kubokawa Tatsuya Название: Shrinkage Estimation for Mean and Covariance Matrices ISBN: 9811515956 ISBN-13(EAN): 9789811515958 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a self-contained introduction to shrinkage estimation for matrix-variate normal distribution models.
Описание: It draws attention to the deficiencies of standard statistical tools when used in the high-dimensional setting, and introduces the basic concepts and major results related to spectral statistics and random matrix theory under high-dimensional asymptotics in an understandable and reader-friendly way.
Автор: Alice Guionnet Название: Large Random Matrices: Lectures on Macroscopic Asymptotics ISBN: 3540698965 ISBN-13(EAN): 9783540698968 Издательство: Springer Рейтинг: Цена: 6282.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Random matrix theory has developed in connection with various fields of mathematics and physics. This title includes notes that emphasize the relation with the problem of enumerating complicated graphs, and the related large deviations questions.
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. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
Автор: Zhidong Bai; Jack W. Silverstein Название: Spectral Analysis of Large Dimensional Random Matrices ISBN: 1461425921 ISBN-13(EAN): 9781461425922 Издательство: Springer Рейтинг: Цена: 24456.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces basic concepts, main results and widely-applied mathematical tools in the spectral analysis of large dimensional random matrices. This updated edition includes two new chapters and summaries from the field of random matrix theory.
Описание: Exploring averaging dynamics in multiagent networked systems, this book offers an in-depth study of stability and other phenomena characterizing the limiting behavior of both deterministic and random averaging dynamics. Includes numerous illustrative examples.
Автор: Gerold Alsmeyer; Matthias L?we Название: Random Matrices and Iterated Random Functions ISBN: 3642388051 ISBN-13(EAN): 9783642388057 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The aim of the workshop was to bring together researchers from two fields of probability theory: random matrix theory and the theory of iterated random functions.
Автор: Ravindra B. Bapat; Steve J. Kirkland; K. Manjunath Название: Combinatorial Matrix Theory and Generalized Inverses of Matrices ISBN: 813221725X ISBN-13(EAN): 9788132217251 Издательство: Springer Рейтинг: Цена: 13275.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book examines two important contemporary areas in linear algebra, namely combinatorial matrix theory and generalized inverses. It covers a wide range of topics of interest such as graph theory, linear algebra, numerical methods and statistical inference.
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