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Jolliffe I. Principal Component Analysis (2ed., Springer, 2002)(518s)

Jolliffe I. Principal Component Analysis (2ed., Springer, 2002)(518s)

Jolliffe I. Principal Component Analysis (2ed., Springer, 2002)(518s)

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466 Indexinfluential observations 43, 81, 123,232, 235, 239, 242, 248–259,265, 268tests of significance 253, 254, 268influential variables 145, 147, 260information see entropyinstability see stabilityinstrumental variables 144, 230,298, 373, 392–394, 401integer-valued PC coefficients, seediscrete PC coefficientsintelligence tests, see childreninteractions 104, 353, 390see also PCs of residualsinter-battery factor analysis 225,399interpolation see smoothing andinterpolationinterpretation of PCs and relatedtechniques 22, 25, 40, 43,44, 56–58, 63–77, 84, 99,142, 166, 191, 217–218, 225,244, 245, 269–298, 333, 339,347, 352, 370, 391, 403, 404over-interpretation 298interpretation of two-dimensionalplotsbiplots 91–103, 106, 107correspondence analysis 103–107PC plots 80–85, 89, 106, 107principal co-ordinate plots 89,106, 107interval data see data given asintervalsinterval estimationfor PC coefficients and variances51–53, 394invariancescale invariance 26under orthogonaltransformations21inverse of correlation matrix 32irregularly-spaced data 320, 331,365, 385isometric vector 53, 344, 345, 347,393, 401, 404Isle of Wight 161, 271jackknife 52, 125, 126, 131, 132,261, 394Kaiser’s rule 114, 115, 123, 126,130–132, 238Kalman filter 335Karhunen-Loève expansion 303,317kriging 317kurtosis 219L 1 -norm PCA 267Lagrange multipliers 5, 6l’analyse des correspondances, seecorrespondence analysislandmark data 210, 323, 345, 346,369Laplace distribution 267large data sets 72, 123, 221, 333,339, 372, 408, 414LASSO (Least Absolute Shrinkageand Selection Operator)167, 284, 286–291last few (low variance) PCs 3, 27,32, 34, 36, 56, 94, 112, 277,347, 352, 374, 377, 378computation 409, 410examples 43, 44, 58, 242–248in canonical correlation analysis223in discriminant analysis 202,204, 205, 207, 208in outlier detection 234, 235,237–239, 242–248, 263, 367in regression 171, 174, 180–182,186–188, 191, 197in variable selection 138,186–188, 191, 197minor component analysis 413treated as noise 53, 118, 128

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