Linear Algebra and Matrix Analysis for Statistics

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Release : 2014-06-06
Genre : Mathematics
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Book Rating : 382/5 ( reviews)

Linear Algebra and Matrix Analysis for Statistics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Linear Algebra and Matrix Analysis for Statistics write by Sudipto Banerjee. This book was released on 2014-06-06. Linear Algebra and Matrix Analysis for Statistics available in PDF, EPUB and Kindle. 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.

Linear Algebra and Matrix Analysis for Statistics

Download Linear Algebra and Matrix Analysis for Statistics PDF Online Free

Author :
Release : 2014-06-06
Genre : Mathematics
Kind :
Book Rating : 247/5 ( reviews)

Linear Algebra and Matrix Analysis for Statistics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Linear Algebra and Matrix Analysis for Statistics write by Sudipto Banerjee. This book was released on 2014-06-06. Linear Algebra and Matrix Analysis for Statistics available in PDF, EPUB and Kindle. Assuming no prior knowledge of linear algebra, this self-contained text 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 covers important topics in linear algebra that are useful for statisticians, including the concept of rank, the fundamental theorem of linear algebra, projectors, and quadratic forms. It also provides an extensive collection of exercises on theoretical concepts and numerical computations.

Matrix Analysis for Statistics

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Release : 2016-06-20
Genre : Mathematics
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Book Rating : 485/5 ( reviews)

Matrix Analysis for Statistics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Matrix Analysis for Statistics write by James R. Schott. This book was released on 2016-06-20. Matrix Analysis for Statistics available in PDF, EPUB and Kindle. 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.

Matrix Algebra

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Release : 2007-07-27
Genre : Computers
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Book Rating : 723/5 ( reviews)

Matrix Algebra - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Matrix Algebra write by James E. Gentle. This book was released on 2007-07-27. Matrix Algebra available in PDF, EPUB and Kindle. 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 Analysis and Applied Linear Algebra

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Release : 2000-06-01
Genre : Mathematics
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Book Rating : 540/5 ( reviews)

Matrix Analysis and Applied Linear Algebra - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Matrix Analysis and Applied Linear Algebra write by Carl D. Meyer. This book was released on 2000-06-01. Matrix Analysis and Applied Linear Algebra available in PDF, EPUB and Kindle. This book avoids the traditional definition-theorem-proof format; instead a fresh approach introduces a variety of problems and examples all in a clear and informal style. The in-depth focus on applications separates this book from others, and helps students to see how linear algebra can be applied to real-life situations. Some of the more contemporary topics of applied linear algebra are included here which are not normally found in undergraduate textbooks. Theoretical developments are always accompanied with detailed examples, and each section ends with a number of exercises from which students can gain further insight. Moreover, the inclusion of historical information provides personal insights into the mathematicians who developed this subject. The textbook contains numerous examples and exercises, historical notes, and comments on numerical performance and the possible pitfalls of algorithms. Solutions to all of the exercises are provided, as well as a CD-ROM containing a searchable copy of the textbook.