Applied Matrix Algebra In The Statistical Sciences

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Linear Algebra and Matrix Analysis for Statistics

Author : Sudipto Banerjee
Publisher : CRC Press
ISBN 13 : 1420095382
Total Pages : 586 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Linear Algebra and Matrix Analysis for Statistics by : Sudipto Banerjee

Download or read book Linear Algebra and Matrix Analysis for Statistics written by Sudipto Banerjee and published by CRC Press. This book was released on 2014-06-06 with total page 586 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear Algebra and Matrix Analysis for Statistics offers a gradual exposition to linear algebra without sacrificing the rigor of the subject. It presents both the vector space approach and the canonical forms in matrix theory. The book is as self-contained as possible, assuming no prior knowledge of linear algebra. The authors first address the rudimentary mechanics of linear systems using Gaussian elimination and the resulting decompositions. They introduce Euclidean vector spaces using less abstract concepts and make connections to systems of linear equations wherever possible. After illustrating the importance of the rank of a matrix, they discuss complementary subspaces, oblique projectors, orthogonality, orthogonal projections and projectors, and orthogonal reduction. The text then shows how the theoretical concepts developed are handy in analyzing solutions for linear systems. The authors also explain how determinants are useful for characterizing and deriving properties concerning matrices and linear systems. They then cover eigenvalues, eigenvectors, singular value decomposition, Jordan decomposition (including a proof), quadratic forms, and Kronecker and Hadamard products. The book concludes with accessible treatments of advanced topics, such as linear iterative systems, convergence of matrices, more general vector spaces, linear transformations, and Hilbert spaces.

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.

Matrix Algebra and Its Applications to Statistics and Econometrics

Author : Calyampudi Radhakrishna Rao
Publisher : World Scientific
ISBN 13 : 9789810232689
Total Pages : 560 pages
Book Rating : 4.2/5 (326 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 World Scientific. This book was released on 1998 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: "I recommend this book for its extensive coverage of topics not easily found elsewhere and for its focus on applications".Zentralblatt MATH"The book is an excellent source on linear algebra, matrix theory and applications in statistics and econometrics, and is unique in many ways. I recommend it to anyone interested in these disciplines, and especially in how they benefit from one another".Statistical Papers, 2000

Introduction to Applied Linear Algebra

Author : Stephen Boyd
Publisher : Cambridge University Press
ISBN 13 : 1316518965
Total Pages : 477 pages
Book Rating : 4.3/5 (165 download)

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Book Synopsis Introduction to Applied Linear Algebra by : Stephen Boyd

Download or read book Introduction to Applied Linear Algebra written by Stephen Boyd and published by Cambridge University Press. This book was released on 2018-06-07 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.

Applied Matrix Algebra in the Statistical Sciences

Author : Alexander Basilevsky
Publisher : North Holland
ISBN 13 :
Total Pages : 416 pages
Book Rating : 4.:/5 (318 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 North Holland. This book was released on 1983 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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.

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."

Linear Models and the Relevant Distributions and Matrix Algebra

Author : David A. Harville
Publisher : CRC Press
ISBN 13 : 1000983757
Total Pages : 242 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis Linear Models and the Relevant Distributions and Matrix Algebra by : David A. Harville

Download or read book Linear Models and the Relevant Distributions and Matrix Algebra written by David A. Harville and published by CRC Press. This book was released on 2023-10-23 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: • Exercises and solutions are included throughout, from both the first and second volume • Includes coverage of additional topics not covered in the first volume • Highly valuable as a reference book for graduate students or researchers

Applied Multivariate Statistics for the Social Sciences

Author : Keenan A. Pituch
Publisher : Routledge
ISBN 13 : 1317805925
Total Pages : 814 pages
Book Rating : 4.3/5 (178 download)

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Book Synopsis Applied Multivariate Statistics for the Social Sciences by : Keenan A. Pituch

Download or read book Applied Multivariate Statistics for the Social Sciences written by Keenan A. Pituch and published by Routledge. This book was released on 2015-12-07 with total page 814 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in its 6th edition, the authoritative textbook Applied Multivariate Statistics for the Social Sciences, continues to provide advanced students with a practical and conceptual understanding of statistical procedures through examples and data-sets from actual research studies. With the added expertise of co-author Keenan Pituch (University of Texas-Austin), this 6th edition retains many key features of the previous editions, including its breadth and depth of coverage, a review chapter on matrix algebra, applied coverage of MANOVA, and emphasis on statistical power. In this new edition, the authors continue to provide practical guidelines for checking the data, assessing assumptions, interpreting, and reporting the results to help students analyze data from their own research confidently and professionally. Features new to this edition include: NEW chapter on Logistic Regression (Ch. 11) that helps readers understand and use this very flexible and widely used procedure NEW chapter on Multivariate Multilevel Modeling (Ch. 14) that helps readers understand the benefits of this "newer" procedure and how it can be used in conventional and multilevel settings NEW Example Results Section write-ups that illustrate how results should be presented in research papers and journal articles NEW coverage of missing data (Ch. 1) to help students understand and address problems associated with incomplete data Completely re-written chapters on Exploratory Factor Analysis (Ch. 9), Hierarchical Linear Modeling (Ch. 13), and Structural Equation Modeling (Ch. 16) with increased focus on understanding models and interpreting results NEW analysis summaries, inclusion of more syntax explanations, and reduction in the number of SPSS/SAS dialogue boxes to guide students through data analysis in a more streamlined and direct approach Updated syntax to reflect newest versions of IBM SPSS (21) /SAS (9.3) A free online resources site at www.routledge.com/9780415836661 with data sets and syntax from the text, additional data sets, and instructor’s resources (including PowerPoint lecture slides for select chapters, a conversion guide for 5th edition adopters, and answers to exercises) Ideal for advanced graduate-level courses in education, psychology, and other social sciences in which multivariate statistics, advanced statistics, or quantitative techniques courses are taught, this book also appeals to practicing researchers as a valuable reference. Pre-requisites include a course on factorial ANOVA and covariance; however, a working knowledge of matrix algebra is not assumed.

Matrix Algebra Useful for Statistics

Author : Shayle R. Searle
Publisher : John Wiley & Sons
ISBN 13 : 1118935144
Total Pages : 517 pages
Book Rating : 4.1/5 (189 download)

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Book Synopsis Matrix Algebra Useful for Statistics by : Shayle R. Searle

Download or read book Matrix Algebra Useful for Statistics written by Shayle R. Searle and published by John Wiley & Sons. This book was released on 2017-05-01 with total page 517 pages. Available in PDF, EPUB and Kindle. Book excerpt: A thoroughly updated guide to matrix algebra and it uses in statistical analysis and features SAS®, MATLAB®, and R throughout This Second Edition addresses matrix algebra that is useful in the statistical analysis of data as well as within statistics as a whole. The material is presented in an explanatory style rather than a formal theorem-proof format and is self-contained. Featuring numerous applied illustrations, numerical examples, and exercises, the book has been updated to include the use of SAS, MATLAB, and R for the execution of matrix computations. In addition, André I. Khuri, who has extensive research and teaching experience in the field, joins this new edition as co-author. The Second Edition also: Contains new coverage on vector spaces and linear transformations and discusses computational aspects of matrices Covers the analysis of balanced linear models using direct products of matrices Analyzes multiresponse linear models where several responses can be of interest Includes extensive use of SAS, MATLAB, and R throughout Contains over 400 examples and exercises to reinforce understanding along with select solutions Includes plentiful new illustrations depicting the importance of geometry as well as historical interludes Matrix Algebra Useful for Statistics, Second Edition is an ideal textbook for advanced undergraduate and first-year graduate level courses in statistics and other related disciplines. The book is also appropriate as a reference for independent readers who use statistics and wish to improve their knowledge of matrix algebra. THE LATE SHAYLE R. SEARLE, PHD, was professor emeritus of biometry at Cornell University. He was the author of Linear Models for Unbalanced Data and Linear Models and co-author of Generalized, Linear, and Mixed Models, Second Edition, Matrix Algebra for Applied Economics, and Variance Components, all published by Wiley. Dr. Searle received the Alexander von Humboldt Senior Scientist Award, and he was an honorary fellow of the Royal Society of New Zealand. ANDRÉ I. KHURI, PHD, is Professor Emeritus of Statistics at the University of Florida. He is the author of Advanced Calculus with Applications in Statistics, Second Edition and co-author of Statistical Tests for Mixed Linear Models, all published by Wiley. Dr. Khuri is a member of numerous academic associations, among them the American Statistical Association and the Institute of Mathematical Statistics.

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.

A Mathematical Primer for Social Statistics

Author : John Fox
Publisher : SAGE
ISBN 13 : 1412960800
Total Pages : 185 pages
Book Rating : 4.4/5 (129 download)

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Book Synopsis A Mathematical Primer for Social Statistics by : John Fox

Download or read book A Mathematical Primer for Social Statistics written by John Fox and published by SAGE. This book was released on 2009 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ideal primer for students and researchers across the social sciences who wish to master the necessary maths in order to pursue studies involving advanced statistical methods

Matrix Algebra

Author : James E. Gentle
Publisher : Springer
ISBN 13 : 3319648675
Total Pages : 664 pages
Book Rating : 4.3/5 (196 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. This book was released on 2017-10-12 with total page 664 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.

Introduction to Applied Numerical Analysis

Author : Richard W. Hamming
Publisher : Courier Corporation
ISBN 13 : 0486485900
Total Pages : 354 pages
Book Rating : 4.4/5 (864 download)

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Book Synopsis Introduction to Applied Numerical Analysis by : Richard W. Hamming

Download or read book Introduction to Applied Numerical Analysis written by Richard W. Hamming and published by Courier Corporation. This book was released on 2012-01-01 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is appropriate for an applied numerical analysis course for upper-level undergraduate and graduate students as well as computer science students. Actual programming is not covered, but an extensive range of topics includes round-off and function evaluation, real zeros of a function, integration, ordinary differential equations, optimization, orthogonal functions, Fourier series, and much more. 1989 edition"--Provided by publisher.

Numerical Linear Algebra for Applications in Statistics

Author : James E. Gentle
Publisher : Springer Science & Business Media
ISBN 13 : 1461206235
Total Pages : 229 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Numerical Linear Algebra for Applications in Statistics by : James E. Gentle

Download or read book Numerical Linear Algebra for Applications in Statistics written by James E. Gentle and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accurate and efficient computer algorithms for factoring matrices, solving linear systems of equations, and extracting eigenvalues and eigenvectors. Regardless of the software system used, the book describes and gives examples of the use of modern computer software for numerical linear algebra. It begins with a discussion of the basics of numerical computations, and then describes the relevant properties of matrix inverses, factorisations, matrix and vector norms, and other topics in linear algebra. The book is essentially self- contained, with the topics addressed constituting the essential material for an introductory course in statistical computing. Numerous exercises allow the text to be used for a first course in statistical computing or as supplementary text for various courses that emphasise computations.

Applied Multivariate Statistics for the Social Sciences

Author : James Stevens
Publisher :
ISBN 13 : 9780805834710
Total Pages : 0 pages
Book Rating : 4.8/5 (347 download)

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Book Synopsis Applied Multivariate Statistics for the Social Sciences by : James Stevens

Download or read book Applied Multivariate Statistics for the Social Sciences written by James Stevens and published by . This book was released on 1996 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book was written for those who will be using, rather than developing, advanced statistical methods. It focuses on a conceptual understanding of the material rather than proving results. It is a graduate level textbook with abundant examples.

Matrix Analysis for Statistics

Author : James R. Schott
Publisher : John Wiley & Sons
ISBN 13 : 1119092469
Total Pages : 698 pages
Book Rating : 4.1/5 (19 download)

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Book Synopsis Matrix Analysis for Statistics by : James R. Schott

Download or read book Matrix Analysis for Statistics written by James R. Schott and published by John Wiley & Sons. This book was released on 2016-05-31 with total page 698 pages. Available in PDF, EPUB and Kindle. Book excerpt: An up-to-date version of the complete, self-contained introduction to matrix analysis theory and practice Providing accessible and in-depth coverage of the most common matrix methods now used in statistical applications, Matrix Analysis for Statistics, Third Edition features an easy-to-follow theorem/proof format. Featuring smooth transitions between topical coverage, the author carefully justifies the step-by-step process of the most common matrix methods now used in statistical applications, including eigenvalues and eigenvectors; the Moore-Penrose inverse; matrix differentiation; and the distribution of quadratic forms. An ideal introduction to matrix analysis theory and practice, Matrix Analysis for Statistics, Third Edition features: • New chapter or section coverage on inequalities, oblique projections, and antieigenvalues and antieigenvectors • Additional problems and chapter-end practice exercises at the end of each chapter • Extensive examples that are familiar and easy to understand • Self-contained chapters for flexibility in topic choice • Applications of matrix methods in least squares regression and the analyses of mean vectors and covariance matrices Matrix Analysis for Statistics, Third Edition is an ideal textbook for upper-undergraduate and graduate-level courses on matrix methods, multivariate analysis, and linear models. The book is also an excellent reference for research professionals in applied statistics. James R. Schott, PhD, is Professor in the Department of Statistics at the University of Central Florida. He has published numerous journal articles in the area of multivariate analysis. Dr. Schott’s research interests include multivariate analysis, analysis of covariance and correlation matrices, and dimensionality reduction techniques.