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

Index 465of correlations between variablesand components 404of data 63, 78–110, 130, 200,201, 212, 214, 215, 217–219,235–236, 242, 244–247, 338,341, 353, 367of intrinsically high-dimensionaldata 107–110group structure 80, 145, 299, 387,398see also cluster analysis,discriminant analysisgrowing scale PCA 334growth curves 328, 330, 331Hilbert EOF analysis see complexPCAHilbert transforms 310, 329, 369history of PCs 6–9Hotelling’s T 2 205, 356, 367, 368household formation 195–198,245–247Householder transformation 410,412how many factors? 116, 126, 130,131, 159, 162how many PCs? 43, 53, 54, 63, 78,111–137, 159, 222, 230, 238,253, 261, 271, 327, 332, 333,338, 385, 387, 395see also parallel analysis, rulesfor selecting PCshypothesis testingfor common PCs 356–360for cumulative proportion oftotal variance 55for equality of multivariatemeans 205for equality of PC variances53–55, 118, 119, 128, 131,132, 136, 276, 394for equivalence of subspaces 360for Hilbert EOFs 311for linear trend in PC variances120, 356for normality 402for outliers 236, 238, 239, 241,367, 368for periodicities 304, 314for specified PC coefficients 53,293, 394for specified PC variances 53,114, 394see also likelihood ratio test,minimum χ 2 testill-conditioning 390see also multicollinearityimage processing 56, 346, 395, 401eigenimages 346Imbrie’s Q-mode method 390imputation of missing values 363,366independent component analysis(ICA) 373, 395, 396indicator matrices 343inference for PCs see estimation,hypothesis testing, intervalestimationinfluence functionadditivity 251deleted empirical influencefunction 251empirical influence function 251for PC coefficients andvariances 253–259local 262sample influence function 249,250, 252for PC coefficients andvariances 253–259for regression coefficients 249standardized influence matrix240theoretical influence functionfor correlation coefficients 250for PC coefficients andvariances 249–251, 253, 263for robust PCA 267for subspaces 252–254