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005 - DATE AND TIME OF LATEST TRANSACTION |
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20140310151446.0 |
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110406s2011 xxu| s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9781441998873 |
|
978-1-4419-9887-3 |
050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
Classification number |
QA276-280 |
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
519.5 |
Edition number |
23 |
264 #1 - |
-- |
New York, NY : |
-- |
Springer New York, |
-- |
2011. |
912 ## - |
-- |
ZDB-2-SMA |
100 1# - MAIN ENTRY--PERSONAL NAME |
Personal name |
Yanai, Haruo. |
Relator term |
author. |
245 10 - IMMEDIATE SOURCE OF ACQUISITION NOTE |
Title |
Projection Matrices, Generalized Inverse Matrices, and Singular Value Decomposition |
Medium |
[electronic resource] / |
Statement of responsibility, etc |
by Haruo Yanai, Kei Takeuchi, Yoshio Takane. |
300 ## - PHYSICAL DESCRIPTION |
Extent |
XII, 236 p. |
Other physical details |
online resource. |
440 1# - SERIES STATEMENT/ADDED ENTRY--TITLE |
Title |
Statistics for Social and Behavioral Sciences |
505 0# - FORMATTED CONTENTS NOTE |
Formatted contents note |
Fundamentals of Linear Algebra -- Projection Matrices -- Generalized Inverse Matrices -- Explicit Representations -- Singular Value Decomposition (SVD) -- Various Applications. |
520 ## - SUMMARY, ETC. |
Summary, etc |
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. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Statistics. |
|
Topical term or geographic name as entry element |
Statistics. |
|
Topical term or geographic name as entry element |
Statistics, general. |
|
Topical term or geographic name as entry element |
Statistics for Life Sciences, Medicine, Health Sciences. |
700 1# - ADDED ENTRY--PERSONAL NAME |
Personal name |
Takeuchi, Kei. |
Relator term |
author. |
|
Personal name |
Takane, Yoshio. |
Relator term |
author. |
710 2# - ADDED ENTRY--CORPORATE NAME |
Corporate name or jurisdiction name as entry element |
SpringerLink (Online service) |
773 0# - HOST ITEM ENTRY |
Title |
Springer eBooks |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
Display text |
Printed edition: |
International Standard Book Number |
9781441998866 |
856 40 - ELECTRONIC LOCATION AND ACCESS |
Uniform Resource Identifier |
http://dx.doi.org/10.1007/978-1-4419-9887-3 |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Source of classification or shelving scheme |
|
Item type |
E-Book |