Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Numerical approximation theory --- Matrix inversion --- Transformations (Mathematics) --- Matrices --- Transformations (Mathématiques) --- Inversion --- 512.64 --- Algorithms --- Differential invariants --- Geometry, Differential --- Inverse matrices --- Inverse of a matrix --- Inversion, Matrix --- Linear operators --- Linear and multilinear algebra. Matrix theory --- Generalized inverses --- Matrix inversion. --- Transformations (Mathematics). --- 512.64 Linear and multilinear algebra. Matrix theory --- MATRIX INVERSION --- Opérateurs linéaires --- Inverses généralisés --- Opérateurs linéaires --- Inverses généralisés

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Regression and the Moore-Penrose pseudoinverse

Matrix inversion. --- Regression analysis. --- Regression analysis --- Matrix inversion --- Mathematical Statistics --- Mathematics --- Physical Sciences & Mathematics --- Analysis, Regression --- Linear regression --- Regression modeling --- Inverse matrices --- Inverse of a matrix --- Inversion, Matrix --- Multivariate analysis --- Structural equation modeling --- Linear operators --- Matrices --- Generalized inverses --- #WWIS:STAT --- 519.233 --- 519.233 Parametric methods --- Parametric methods --- Pseudoinverses --- Pseudo-inverses. --- Analyse de régression --- Inversion --- ELSEVIER-B EPUB-LIV-FT --- Regression Analysis

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

In 1990, the National Science Foundation recommended that every college mathematics curriculum should include a second course in linear algebra. In answer to this recommendation, Matrix Theory: From Generalized Inverses to Jordan Form provides the material for a second semester of linear algebra that probes introductory linear algebra concepts while also exploring topics not typically covered in a sophomore-level class. Tailoring the material to advanced undergraduate and beginning graduate students, the authors offer instructors flexibility in choosing topics from the book. The text first focuses on the central problem of linear algebra: solving systems of linear equations. It then discusses LU factorization, derives Sylvester's rank formula, introduces full-rank factorization, and describes generalized inverses. After discussions on norms, QR factorization, and orthogonality, the authors prove the important spectral theorem. They also highlight the primary decomposition theorem, Schur's triangularization theorem, singular value decomposition, and the Jordan canonical form theorem. The book concludes with a chapter on multilinear algebra. With this classroom-tested text students can delve into elementary linear algebra ideas at a deeper level and prepare for further study in matrix theory and abstract algebra.

Algebra --- Matrices --- Algebras, Linear --- Matrix inversion --- 512.643 --- Matrices and linear mappings. Matrix theory. Determinants. Eigenvalues --- 512.643 Matrices and linear mappings. Matrix theory. Determinants. Eigenvalues --- Inverse matrices --- Inverse of a matrix --- Inversion, Matrix --- Linear operators --- Algebra, Matrix --- Cracovians (Mathematics) --- Matrix algebra --- Matrixes (Algebra) --- Algebra, Abstract --- Algebra, Universal --- Linear algebra --- Generalized spaces --- Mathematical analysis --- Calculus of operations --- Line geometry --- Topology --- Generalized inverses --- Matrices - Textbooks --- Algebras, Linear - Textbooks --- Matrix inversion - Textbooks

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Numerical solutions of algebraic equations --- Error analysis (Mathematics) --- Estimation theory --- 519.22 --- Matrix inversion --- 512.64 --- Inverse matrices --- Inverse of a matrix --- Inversion, Matrix --- Linear operators --- Matrices --- Estimating techniques --- Least squares --- Mathematical statistics --- Stochastic processes --- Errors, Theory of --- Instrumental variables (Statistics) --- Numerical analysis --- Statistics --- Statistical theory. Statistical models. Mathematical statistics in general --- Linear and multilinear algebra. Matrix theory --- Generalized inverses --- Estimation theory. --- Matrix inversion. --- Error analysis (Mathematics). --- 512.64 Linear and multilinear algebra. Matrix theory --- 519.22 Statistical theory. Statistical models. Mathematical statistics in general --- Opérateurs linéaires --- Inverses généralisés --- Calcul d'erreur. --- Moindres carrés. --- Opérateurs linéaires --- Moindres carrés. --- Inverses généralisés

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Aside from distribution theory, projections and the singular value decomposition (SVD) are the two most important concepts for understanding the basic mechanism of multivariate analysis. The former underlies the least squares estimation in regression analysis, which is essentially a projection of one subspace onto another, and the latter underlies principal component analysis, which seeks to find a subspace that captures the largest variability in the original space. This book is about projections and SVD. A thorough discussion of generalized inverse (g-inverse) matrices is also given because it is closely related to the former. The book provides systematic and in-depth accounts of these concepts from a unified viewpoint of linear transformations finite dimensional vector spaces. More specially, it shows that projection matrices (projectors) and g-inverse matrices can be defined in various ways so that a vector space is decomposed into a direct-sum of (disjoint) subspaces. Projection Matrices, Generalized Inverse Matrices, and Singular Value Decomposition will be useful for researchers, practitioners, and students in applied mathematics, statistics, engineering, behaviormetrics, and other fields.

Mathematical statistics. --- Matrices. --- Multivariate analysis. --- Multivariate analysis -- Problems, exercises, etc. --- Singular value decomposition --- Matrix inversion --- Algebras, Linear --- Mathematics --- Physical Sciences & Mathematics --- Algebra --- Mathematical Statistics --- Decomposition method. --- Matrix inversion. --- Algebras, Linear. --- Linear algebra --- Inverse matrices --- Inverse of a matrix --- Inversion, Matrix --- Method, Decomposition --- Algebra, Matrix --- Cracovians (Mathematics) --- Matrix algebra --- Matrixes (Algebra) --- Statistics. --- Statistics, general. --- Statistics for Life Sciences, Medicine, Health Sciences. --- Algebra, Universal --- Generalized spaces --- Mathematical analysis --- Calculus of operations --- Line geometry --- Topology --- Linear operators --- Matrices --- Operations research --- Programming (Mathematics) --- System analysis --- Algebra, Abstract --- Generalized inverses --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Econometrics --- Statistics .