Author: Haruo Yanai
Edition: 2011
Publisher: Springer
Binding: Hardcover
ISBN: 1441998861
Projection Matrices, Generalized Inverse Matrices, and Singular Value Decomposition (Statistics for Social and Behavioral Sciences)
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. Medical books Projection Matrices, Generalized Inverse Matrices, and Singular Value Decomposition . 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 Medical books Projection Matrices, Generalized Inverse Matrices, And Singular Value Decomp. Electronics Cameras Computers Software Housewares Sports DVDs Music Books Games Toys in titles descriptions Company Info |Checkout Info |Shipping Info |Return Policy |FAQ's Add us as a favorite seller By continuing with your purchase using the eBay Buy It Now button, you agree to the Buy Terms of Use at http://stores.ebay.com/Buys-Internet-Superstore/Terms.html . Projection Matrices, Generalized Inverse Matrices, and Singular Value Decomposition - Yanai, Haruo/ Takeuchi, Kei/ Takane, Yoshio THI
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Electronics Cameras Computers Software Housewares Sports DVDs Music Books Games Toys in titles descriptions Company Info |Checkout Info |Shipping Info |Return Policy |FAQ's Add us as a favorite seller By continuing with your purchase using the eBay Buy It Now button, you agree to the Buy Terms of Use at http://stores.ebay.com/Buys-Internet-Superstore/Terms.html . Projection Matrices, Generalized Inverse Matrices, and Singular Value Decomposition - Yanai, Haruo/ Takeuchi, Kei/ Takane, Yoshio THI
Springer 9781441998866 Projection Matrices, Generalized Inverse Matrices, and Singular Value Decomposition Description *Author: Yanai, Haruo/ Takeuchi, Kei/ Takane, Yoshio *Series Title: Statistics for Social and Behavioral Sciences *Binding Type: Hardcover *Number of Pages: 234 *Publication Date: 2011/04/01 *Language: English *Dimensions: 6.62 x 9.48 x 0.82 inches SKU: UBM9781441998866 Payment We accept payment via PayPal, Mastercard, Visa, American Express, Discover and PayPals Bill Me La
Contributors: Haruo Yanai - Author. Format: Hardcover
Springer-Verlag New York Inc. | 2011 | 248 pages | ISBN-13: 9781441998866 | ISBN-10: 1441998861 | You save 20%
Medical Book Projection Matrices, Generalized Inverse Matrices, and Singular Value Decomposition
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.
