Principal component analysis / (Record no. 15351)

MARC details
000 -LEADER
fixed length control field 02209cam a2200253 a 4500
001 - CONTROL NUMBER
control field TB12810
003 - CONTROL NUMBER IDENTIFIER
control field IN-BhIIT
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20260212165753.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 020123s2002 nyua b 001 0 eng
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9780387954424 (pbk.)
040 ## - CATALOGING SOURCE
Original cataloging agency IN-BhIIT
041 ## - LANGUAGE CODE
Language code of text eng
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.535
Book number JOL/P
100 1# - MAIN ENTRY--AUTHOR NAME
Personal name Jolliffe, I. T.
Relator term Author
245 10 - TITLE STATEMENT
Title Principal component analysis /
Statement of responsibility, etc I.T. Jolliffe.
250 ## - EDITION STATEMENT
Edition statement 2nd ed.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication New York :
Name of publisher Springer,
Year of publication 2002.
300 ## - PHYSICAL DESCRIPTION
Number of Pages xxix, 487 p. :
Other physical details(ill.) ill. ;
Dimensions(size) 24 cm.
490 ## - SERIES STATEMENT
Series statement Springer series in statistics
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references and indexes.
520 ## - SUMMARY, ETC.
Summary, etc Principal component analysis is probably the oldest and best known of the It was first introduced by Pearson (1901), techniques ofmultivariate analysis. and developed independently by Hotelling (1933). Like many multivariate methods, it was not widely used until the advent of electronic computers, but it is now weIl entrenched in virtually every statistical computer package. The central idea of principal component analysis is to reduce the dimen?? sionality of a data set in which there are a large number of interrelated variables, while retaining as much as possible of the variation present in the data set. This reduction is achieved by transforming to a new set of variables, the principal components, which are uncorrelated, and which are ordered so that the first few retain most of the variation present in all of the original variables. Computation of the principal components reduces to the solution of an eigenvalue-eigenvector problem for a positive-semidefinite symmetrie matrix. Thus, the definition and computation of principal components are straightforward but, as will be seen, this apparently simple technique has a wide variety of different applications, as weIl as a number of different deri?? vations. Any feelings that principal component analysis is a narrow subject should soon be dispelled by the present book; indeed some quite broad topics which are related to principal component analysis receive no more than a brief mention in the final two chapters.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Mathematics
General subdivision Statistical Mathematics
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Text Book
Holdings
Withdrawn status Lost status Damaged status Not for loan Collection code Home library Current library Date acquired Source of acquisition Cost, normal purchase price Full call number Accession Number Cost, replacement price Price effective from Koha item type
Not withdrawn Not Lost not damaged   SEOCS Central Library, IIT Bhubaneswar Central Library, IIT Bhubaneswar 10/02/2026 32 23333.67 519.535 JOL/P TB12811 31963.93 10/02/2026 Text Book
Not withdrawn Not Lost not damaged   SEOCS Central Library, IIT Bhubaneswar Central Library, IIT Bhubaneswar 10/02/2026 32 23333.67 519.535 JOL/P TB12810 31963.93 10/02/2026 Course Reserve

Central Library, Indian Institute of Technology Bhubaneswar, 4th Floor, Administrative Building, Argul, Khordha, PIN-752050, Odisha, India
Phone: +91-674-7138750 | Email: circulation.library@iitbbs.ac.in (For circulation related queries),
Email: info.library@iitbbs.ac.in (For other queries)