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

Index 459116, 127-130, 133, 270, 274,284, 289, 294–297, 302–317,332, 354, 362, 364, 385see also meteorology andclimatologyautocorrelation/autocovariance129, 149, 298, 335, 336autoregressive processesARMA models 336, 337first order 301, 327, 334, 335multivariate first order 302, 308auxiliaries 399Bartlett’s test see hypothesistesting for equality of PCvariancesbasis functions 318–320, 325, 327Fourier basis 319spline basis 320, 322, 325, 331Bayesian inference 222, 395in factor analysis 155in regression 177, 179posterior distribution 56, 126prior distribution 60, 126, 179using PCs 56, 60Behrens-Fisher problem,multivariate 356best-fittinglines, planes and hyperplanes 7,36, 189, 389subspaces 34–36, 78, 80, 87, 342best linear approximation to PCsusing subset of variables294best linear predictors 16, 17, 392between–group variation 202, 203,209, 220, 399between–treatment (and –block)PCs 352biased regression methods 167,168, 171, 172, 177–179,183–185, 230, 286see also PC regression, ridgeregression, shrinkagemethodsbinary variables 68, 88, 339, 340,343, 346presence/absence data 105, 107,390biological applications 9, 57, 64,90, 390aphids 122, 145-147, 214, 219birdsIrish wetland birds 105–106seabird communities 214diving seals 316, 323see also ecology, size and shapePCsbiplots 79, 90–103, 132, 230, 342,353, 408bimodel 91classical 90, 101coefficient of variation 102, 389computation 413correspondence analysis 95, 96generalized 102interpolation and prediction 102,382non-linear 102, 381, 382robust 102, 265symmetric 96bisection method 411Bonferroni bound 248bootstrap estimation 49, 112, 117,125, 126, 261, 267, 314, 394confidence intervals 52, 118, 126,331in quality control 368non-parametric 52of residuals 125, 377parametric 52resampling in blocks 360boxplots 295of PC scores 125, 235branch-and-bound algorithm 284broken stick model 115, 130, 132,143Burt matrix 343calibration 190