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

472 Indexrelationships (QSAR), seechemistryquartimin/quartimax rotation 153,154, 162–165, 270, 271, 277,278quaternion valued data 370ranked data 267, 338, 340, 341,348, 349, 388rank correlation 341reciprocal averaging, see scaling orordinationred noise 301, 304, 307, 314reduced rank regression 229, 230,331, 353, 392, 401softly shrunk reduced rankregression 230reduction of dimensionality, seedimensionality reductionredundancy analysis 225–230, 331,393, 401redundancy coefficient/index 226,227redundant variables, seedimensionality reductionregionalization studies 213, 294regression analysis 13, 32, 33, 74,111, 112, 121, 127, 129, 137,144, 145, 157, 167–199, 202,205, 223, 227, 239, 240, 284,286, 288, 290, 294, 304, 326,337, 352, 363, 366, 368, 378,390, 399, 412computation 46, 168, 170, 173,182, 412influence function 249, 250interpretation 46, 168, 170, 173,182, 412residuals 127, 399variable selection 111, 112, 137,145, 167, 172, 182, 185–188,190, 191, 194, 197, 198, 286see also biased regressionmethods, econometrics,influence functions,latent root regression,least squares estimation,multivariate regression, PCregression, point estimation,reduced rank regression,ridge regression, robustregression, selection ofvariablesregression components 403regression tree 185regularized discriminant analysis205, 207, 208reification 269repeatability of PCA 261, 394repeated measures, see longitudinaldatarescaled PCs 403, 404residual variation 16, 17, 108, 114,129, 220, 240, 290, 399see also error covariance matrix,PCA of residualsresiduals in a contingency table,see interactionsresponse variables 227–230PCs of predicted responses 228,230see also regression analysisrestricted PC regression 184ridge regression 167, 178, 179, 181,185, 190, 364road running, see athleticsrobust estimation 232, 262–268in functional PCA 266, 316, 327in non-linear PCA 376in regression 264, 366of biplots 102, 265of covariance/correlationmatrices 264, 265–267, 363,364, 394of distributions of PCs 267of means 241, 264, 265of PCs 50, 61, 233, 235, 263–268,356, 366, 368, 394, 401of scale 266see also M-estimators, minimum