A Matrix Handbook For Statisticians

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A Matrix Handbook for Statisticians

Author : George A. F. Seber
Publisher : John Wiley & Sons
ISBN 13 : 0470226781
Total Pages : 592 pages
Book Rating : 4.4/5 (72 download)

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Book Synopsis A Matrix Handbook for Statisticians by : George A. F. Seber

Download or read book A Matrix Handbook for Statisticians written by George A. F. Seber and published by John Wiley & Sons. This book was released on 2008-01-28 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive, must-have handbook of matrix methods with a unique emphasis on statistical applications This timely book, A Matrix Handbook for Statisticians, provides a comprehensive, encyclopedic treatment of matrices as they relate to both statistical concepts and methodologies. Written by an experienced authority on matrices and statistical theory, this handbook is organized by topic rather than mathematical developments and includes numerous references to both the theory behind the methods and the applications of the methods. A uniform approach is applied to each chapter, which contains four parts: a definition followed by a list of results; a short list of references to related topics in the book; one or more references to proofs; and references to applications. The use of extensive cross-referencing to topics within the book and external referencing to proofs allows for definitions to be located easily as well as interrelationships among subject areas to be recognized. A Matrix Handbook for Statisticians addresses the need for matrix theory topics to be presented together in one book and features a collection of topics not found elsewhere under one cover. These topics include: Complex matrices A wide range of special matrices and their properties Special products and operators, such as the Kronecker product Partitioned and patterned matrices Matrix analysis and approximation Matrix optimization Majorization Random vectors and matrices Inequalities, such as probabilistic inequalities Additional topics, such as rank, eigenvalues, determinants, norms, generalized inverses, linear and quadratic equations, differentiation, and Jacobians, are also included. The book assumes a fundamental knowledge of vectors and matrices, maintains a reasonable level of abstraction when appropriate, and provides a comprehensive compendium of linear algebra results with use or potential use in statistics. A Matrix Handbook for Statisticians is an essential, one-of-a-kind book for graduate-level courses in advanced statistical studies including linear and nonlinear models, multivariate analysis, and statistical computing. It also serves as an excellent self-study guide for statistical researchers.

Matrices for Statistics

Author : M. J. R. Healy
Publisher : Oxford University Press
ISBN 13 : 9780198507024
Total Pages : 164 pages
Book Rating : 4.5/5 (7 download)

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Book Synopsis Matrices for Statistics by : M. J. R. Healy

Download or read book Matrices for Statistics written by M. J. R. Healy and published by Oxford University Press. This book was released on 2000 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a concise introduction to the basis of matrix theory. The text of the first edition has been re-written and revised to take account of recent developments in statistical practice. The more difficult topics have been expanded and the mathematical explanations have been simplified. A new chapter has been included, at readers' request, to cover such topics as vectorising, matrix calculus and complex numbers.

Matrix Algebra

Author : James E. Gentle
Publisher : Springer Science & Business Media
ISBN 13 : 0387708723
Total Pages : 536 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis Matrix Algebra by : James E. Gentle

Download or read book Matrix Algebra written by James E. Gentle and published by Springer Science & Business Media. This book was released on 2007-07-27 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: Matrix algebra is one of the most important areas of mathematics for data analysis and for statistical theory. This much-needed work presents the relevant aspects of the theory of matrix algebra for applications in statistics. It moves on to consider the various types of matrices encountered in statistics, such as projection matrices and positive definite matrices, and describes the special properties of those matrices. Finally, it covers numerical linear algebra, beginning with a discussion of the basics of numerical computations, and following up with accurate and efficient algorithms for factoring matrices, solving linear systems of equations, and extracting eigenvalues and eigenvectors.

Handbook of Matrices

Author : Helmut L?tkepohl
Publisher :
ISBN 13 :
Total Pages : 328 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Handbook of Matrices by : Helmut L?tkepohl

Download or read book Handbook of Matrices written by Helmut L?tkepohl and published by . This book was released on 1996-11-05 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Matrices are used in many areas including statistics, natural sciences, econometrics, maths & engineering. This book provides a collection of results for easy reference in one source, along with a comprehensive dictionary of matrices & related terms.

Basics of Matrix Algebra for Statistics with R

Author : Nick Fieller
Publisher : CRC Press
ISBN 13 : 1315360055
Total Pages : 208 pages
Book Rating : 4.3/5 (153 download)

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Book Synopsis Basics of Matrix Algebra for Statistics with R by : Nick Fieller

Download or read book Basics of Matrix Algebra for Statistics with R written by Nick Fieller and published by CRC Press. This book was released on 2018-09-03 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Thorough Guide to Elementary Matrix Algebra and Implementation in R Basics of Matrix Algebra for Statistics with R provides a guide to elementary matrix algebra sufficient for undertaking specialized courses, such as multivariate data analysis and linear models. It also covers advanced topics, such as generalized inverses of singular and rectangular matrices and manipulation of partitioned matrices, for those who want to delve deeper into the subject. The book introduces the definition of a matrix and the basic rules of addition, subtraction, multiplication, and inversion. Later topics include determinants, calculation of eigenvectors and eigenvalues, and differentiation of linear and quadratic forms with respect to vectors. The text explores how these concepts arise in statistical techniques, including principal component analysis, canonical correlation analysis, and linear modeling. In addition to the algebraic manipulation of matrices, the book presents numerical examples that illustrate how to perform calculations by hand and using R. Many theoretical and numerical exercises of varying levels of difficulty aid readers in assessing their knowledge of the material. Outline solutions at the back of the book enable readers to verify the techniques required and obtain numerical answers. Avoiding vector spaces and other advanced mathematics, this book shows how to manipulate matrices and perform numerical calculations in R. It prepares readers for higher-level and specialized studies in statistics.

Spectral Analysis of Large Dimensional Random Matrices

Author : Zhidong Bai
Publisher : Springer Science & Business Media
ISBN 13 : 1441906614
Total Pages : 560 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Spectral Analysis of Large Dimensional Random Matrices by : Zhidong Bai

Download or read book Spectral Analysis of Large Dimensional Random Matrices written by Zhidong Bai and published by Springer Science & Business Media. This book was released on 2009-12-10 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of the book is to introduce basic concepts, main results, and widely applied mathematical tools in the spectral analysis of large dimensional random matrices. The core of the book focuses on results established under moment conditions on random variables using probabilistic methods, and is thus easily applicable to statistics and other areas of science. The book introduces fundamental results, most of them investigated by the authors, such as the semicircular law of Wigner matrices, the Marcenko-Pastur law, the limiting spectral distribution of the multivariate F matrix, limits of extreme eigenvalues, spectrum separation theorems, convergence rates of empirical distributions, central limit theorems of linear spectral statistics, and the partial solution of the famous circular law. While deriving the main results, the book simultaneously emphasizes the ideas and methodologies of the fundamental mathematical tools, among them being: truncation techniques, matrix identities, moment convergence theorems, and the Stieltjes transform. Its treatment is especially fitting to the needs of mathematics and statistics graduate students and beginning researchers, having a basic knowledge of matrix theory and an understanding of probability theory at the graduate level, who desire to learn the concepts and tools in solving problems in this area. It can also serve as a detailed handbook on results of large dimensional random matrices for practical users. This second edition includes two additional chapters, one on the authors' results on the limiting behavior of eigenvectors of sample covariance matrices, another on applications to wireless communications and finance. While attempting to bring this edition up-to-date on recent work, it also provides summaries of other areas which are typically considered part of the general field of random matrix theory.

Matrix Algebra From a Statistician's Perspective

Author : David A. Harville
Publisher : Springer Science & Business Media
ISBN 13 : 0387783563
Total Pages : 639 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis Matrix Algebra From a Statistician's Perspective by : David A. Harville

Download or read book Matrix Algebra From a Statistician's Perspective written by David A. Harville and published by Springer Science & Business Media. This book was released on 2008-06-27 with total page 639 pages. Available in PDF, EPUB and Kindle. Book excerpt: A knowledge of matrix algebra is a prerequisite for the study of much of modern statistics, especially the areas of linear statistical models and multivariate statistics. This reference book provides the background in matrix algebra necessary to do research and understand the results in these areas. Essentially self-contained, the book is best-suited for a reader who has had some previous exposure to matrices. Solultions to the exercises are available in the author's "Matrix Algebra: Exercises and Solutions."

Computational Statistics with R

Author :
Publisher : Elsevier
ISBN 13 : 044463441X
Total Pages : 413 pages
Book Rating : 4.4/5 (446 download)

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Book Synopsis Computational Statistics with R by :

Download or read book Computational Statistics with R written by and published by Elsevier. This book was released on 2014-11-27 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: R is open source statistical computing software. Since the R core group was formed in 1997, R has been extended by a very large number of packages with extensive documentation along with examples freely available on the internet. It offers a large number of statistical and numerical methods and graphical tools and visualization of extraordinarily high quality. R was recently ranked in 14th place by the Transparent Language Popularity Index and 6th as a scripting language, after PHP, Python, and Perl. The book is designed so that it can be used right away by novices while appealing to experienced users as well. Each article begins with a data example that can be downloaded directly from the R website. Data analysis questions are articulated following the presentation of the data. The necessary R commands are spelled out and executed and the output is presented and discussed. Other examples of data sets with a different flavor and different set of commands but following the theme of the article are presented as well. Each chapter predents a hands-on-experience. R has superb graphical outlays and the book brings out the essentials in this arena. The end user can benefit immensely by applying the graphics to enhance research findings. The core statistical methodologies such as regression, survival analysis, and discrete data are all covered. Addresses data examples that can be downloaded directly from the R website No other source is needed to gain practical experience Focus on the essentials in graphical outlays

Handbook of Statistical Analyses Using Stata

Author : Brian S. Everitt
Publisher : CRC Press
ISBN 13 : 1466580577
Total Pages : 354 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Handbook of Statistical Analyses Using Stata by : Brian S. Everitt

Download or read book Handbook of Statistical Analyses Using Stata written by Brian S. Everitt and published by CRC Press. This book was released on 2006-11-15 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: With each new release of Stata, a comprehensive resource is needed to highlight the improvements as well as discuss the fundamentals of the software. Fulfilling this need, AHandbook of Statistical Analyses Using Stata, Fourth Edition has been fully updated to provide an introduction to Stata version 9. This edition covers many

Handbook of Parallel Computing and Statistics

Author : Erricos John Kontoghiorghes
Publisher : CRC Press
ISBN 13 : 9781420028683
Total Pages : 560 pages
Book Rating : 4.0/5 (286 download)

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Book Synopsis Handbook of Parallel Computing and Statistics by : Erricos John Kontoghiorghes

Download or read book Handbook of Parallel Computing and Statistics written by Erricos John Kontoghiorghes and published by CRC Press. This book was released on 2005-12-21 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technological improvements continue to push back the frontier of processor speed in modern computers. Unfortunately, the computational intensity demanded by modern research problems grows even faster. Parallel computing has emerged as the most successful bridge to this computational gap, and many popular solutions have emerged based on its concepts

Comparisons of Stochastic Matrices with Applications in Information Theory, Statistics, Economics and Population

Author : JOEL COHEN
Publisher : Springer Science & Business Media
ISBN 13 : 9780817640828
Total Pages : 170 pages
Book Rating : 4.6/5 (48 download)

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Book Synopsis Comparisons of Stochastic Matrices with Applications in Information Theory, Statistics, Economics and Population by : JOEL COHEN

Download or read book Comparisons of Stochastic Matrices with Applications in Information Theory, Statistics, Economics and Population written by JOEL COHEN and published by Springer Science & Business Media. This book was released on 1998-09-29 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: Some of the possible implications among these comparisons remain open questions. The results in this book establish a new field of investigation for both mathematicians and scientific users interested in the variations among multiple probability distributions.

Numerical Analysis for Statisticians

Author : Kenneth Lange
Publisher : Springer Science & Business Media
ISBN 13 : 1441959459
Total Pages : 606 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Numerical Analysis for Statisticians by : Kenneth Lange

Download or read book Numerical Analysis for Statisticians written by Kenneth Lange and published by Springer Science & Business Media. This book was released on 2010-05-17 with total page 606 pages. Available in PDF, EPUB and Kindle. Book excerpt: Numerical analysis is the study of computation and its accuracy, stability and often its implementation on a computer. This book focuses on the principles of numerical analysis and is intended to equip those readers who use statistics to craft their own software and to understand the advantages and disadvantages of different numerical methods.

Applied Matrix Algebra in the Statistical Sciences

Author : Alexander Basilevsky
Publisher : Courier Corporation
ISBN 13 : 0486153371
Total Pages : 412 pages
Book Rating : 4.4/5 (861 download)

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Book Synopsis Applied Matrix Algebra in the Statistical Sciences by : Alexander Basilevsky

Download or read book Applied Matrix Algebra in the Statistical Sciences written by Alexander Basilevsky and published by Courier Corporation. This book was released on 2013-01-18 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive text offers teachings relevant to both applied and theoretical branches of matrix algebra and provides a bridge between linear algebra and statistical models. Appropriate for advanced undergraduate and graduate students. 1983 edition.

Linear Models in Statistics

Author : Alvin C. Rencher
Publisher : John Wiley & Sons
ISBN 13 : 0470192607
Total Pages : 690 pages
Book Rating : 4.4/5 (71 download)

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Book Synopsis Linear Models in Statistics by : Alvin C. Rencher

Download or read book Linear Models in Statistics written by Alvin C. Rencher and published by John Wiley & Sons. This book was released on 2008-01-07 with total page 690 pages. Available in PDF, EPUB and Kindle. Book excerpt: The essential introduction to the theory and application of linear models—now in a valuable new edition Since most advanced statistical tools are generalizations of the linear model, it is neces-sary to first master the linear model in order to move forward to more advanced concepts. The linear model remains the main tool of the applied statistician and is central to the training of any statistician regardless of whether the focus is applied or theoretical. This completely revised and updated new edition successfully develops the basic theory of linear models for regression, analysis of variance, analysis of covariance, and linear mixed models. Recent advances in the methodology related to linear mixed models, generalized linear models, and the Bayesian linear model are also addressed. Linear Models in Statistics, Second Edition includes full coverage of advanced topics, such as mixed and generalized linear models, Bayesian linear models, two-way models with empty cells, geometry of least squares, vector-matrix calculus, simultaneous inference, and logistic and nonlinear regression. Algebraic, geometrical, frequentist, and Bayesian approaches to both the inference of linear models and the analysis of variance are also illustrated. Through the expansion of relevant material and the inclusion of the latest technological developments in the field, this book provides readers with the theoretical foundation to correctly interpret computer software output as well as effectively use, customize, and understand linear models. This modern Second Edition features: New chapters on Bayesian linear models as well as random and mixed linear models Expanded discussion of two-way models with empty cells Additional sections on the geometry of least squares Updated coverage of simultaneous inference The book is complemented with easy-to-read proofs, real data sets, and an extensive bibliography. A thorough review of the requisite matrix algebra has been addedfor transitional purposes, and numerous theoretical and applied problems have been incorporated with selected answers provided at the end of the book. A related Web site includes additional data sets and SAS® code for all numerical examples. Linear Model in Statistics, Second Edition is a must-have book for courses in statistics, biostatistics, and mathematics at the upper-undergraduate and graduate levels. It is also an invaluable reference for researchers who need to gain a better understanding of regression and analysis of variance.

Matrix Algebra for Linear Models

Author : Marvin H. J. Gruber
Publisher : John Wiley & Sons
ISBN 13 : 1118592557
Total Pages : 391 pages
Book Rating : 4.1/5 (185 download)

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Book Synopsis Matrix Algebra for Linear Models by : Marvin H. J. Gruber

Download or read book Matrix Algebra for Linear Models written by Marvin H. J. Gruber and published by John Wiley & Sons. This book was released on 2013-12-31 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: A self-contained introduction to matrix analysis theory and applications in the field of statistics Comprehensive in scope, Matrix Algebra for Linear Models offers a succinct summary of matrix theory and its related applications to statistics, especially linear models. The book provides a unified presentation of the mathematical properties and statistical applications of matrices in order to define and manipulate data. Written for theoretical and applied statisticians, the book utilizes multiple numerical examples to illustrate key ideas, methods, and techniques crucial to understanding matrix algebra’s application in linear models. Matrix Algebra for Linear Models expertly balances concepts and methods allowing for a side-by-side presentation of matrix theory and its linear model applications. Including concise summaries on each topic, the book also features: Methods of deriving results from the properties of eigenvalues and the singular value decomposition Solutions to matrix optimization problems for obtaining more efficient biased estimators for parameters in linear regression models A section on the generalized singular value decomposition Multiple chapter exercises with selected answers to enhance understanding of the presented material Matrix Algebra for Linear Models is an ideal textbook for advanced undergraduate and graduate-level courses on statistics, matrices, and linear algebra. The book is also an excellent reference for statisticians, engineers, economists, and readers interested in the linear statistical model.

Matrix Algebra and Its Applications to Statistics and Econometrics

Author : Calyampudi Radhakrishna Rao
Publisher :
ISBN 13 :
Total Pages : 535 pages
Book Rating : 4.:/5 (847 download)

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Book Synopsis Matrix Algebra and Its Applications to Statistics and Econometrics by : Calyampudi Radhakrishna Rao

Download or read book Matrix Algebra and Its Applications to Statistics and Econometrics written by Calyampudi Radhakrishna Rao and published by . This book was released on 1998 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Learning Statistics with R

Author : Daniel Navarro
Publisher : Lulu.com
ISBN 13 : 1326189727
Total Pages : 617 pages
Book Rating : 4.3/5 (261 download)

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Book Synopsis Learning Statistics with R by : Daniel Navarro

Download or read book Learning Statistics with R written by Daniel Navarro and published by Lulu.com. This book was released on 2013-01-13 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com