02528cam a2200277 a 4500001000800000003000900008005001700017008004100034020002500075040001300100041000800113082001900121100003500140245005100175250001200226260003300238300003500271490003400306504005300340520149000393650004801883942000701931999001701938952014701955952014802102TB12810IN-BhIIT20260212165753.0020123s2002    nyua     b    001 0 eng    a9780387954424 (pbk.)  aIN-BhIIT  aeng00a519.535bJOL/P1 aJolliffe, I. T.eAuthor92722810aPrincipal component analysis /cI.T. Jolliffe.  a2nd ed.  aNew York :bSpringer,c2002.  axxix, 487 p. :bill. ;c24 cm.  aSpringer series in statistics  aIncludes bibliographical references and indexes.  aPrincipal 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. 0aMathematicsxStatistical Mathematics927229  cTB  c15351d15351  00102ddc40708SEOCSaCLIITBBSbCLIITBBSd2026-02-10e32g23333.67l0o519.535 JOL/PpTB12811r2026-02-10 00:00:00v31963.93w2026-02-10yTB  00102ddc40708SEOCSaCLIITBBSbCLIITBBSd2026-02-10e32g23333.67l0o519.535 JOL/PpTB12810r2026-02-10 00:00:00v31963.93w2026-02-10yRES