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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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Index 475spatial correlation/covariance 297,302, 317, 333–335intrinsic correlation model 334isotropy and anisotropy 297, 334linear model of co-regionalization334non-stationarity 297spatial data 71–74, 130, 274, 275,278–283, 289, 294, 295, 300,302, 307–317, 320, 328, 329,332–339, 364, 365, 370, 385,398spatial lattice 368spatial domain, size and shape297, 334species abundance data 105–107,224–225, 339, 371, 372,389–391between- and within-site speciesdiversity 372, 389spectral decomposition of a matrix13, 14, 31, 37, 44, 46, 86,87, 101, 113, 170, 171, 266,333, 344, 355, 368, 395, 404weighted 207spectral/spectrum analysis of atime series 300, 301, 311,337spectrophotometry, see chemistrysphering data 219splines see smoothing andinterpolationstability/instabilityof PC subspaces 42, 53, 259, 261of PCs and their variances 76,81, 118, 126, 127, 232,259–263, 267, 297of spatial fields 130see also influence function,influential variablesstandard errors for PC coefficientsand variances 50, 52standardized variables 21, 24–27,42, 112, 169, 211, 250, 274,388, 389statistical physics 266, 401statistical process control 114, 184,240, 333, 337, 339, 366–369,381, 398CUSUM charts 367exponentially-weighted movingprincipal components 337,368squared prediction error (SPE)367, 368stochastic complexity 19, 39, 395strategies for selecting PCs inregressionsee selection of subsets of PCsstructural relationships, seefunctional and structuralrelationshipsstructure of PCs 24, 27, 28, 30,56–59PCs similar to original variables22, 24, 40, 41, 43, 56, 115,127, 134, 135, 146, 149, 159,211, 259see also contrasts betweenvariables, interpretationof PCs, patternedcorrelation/covariancematrices, PC coefficients,size and shape PCsstudent anatomical measurements,see anatomicalmeasurementsSturm sequences 411subjective PCs 404subset selection, see selection ofsubsets of PCs, selection ofvariablessubspacesspanned by subsets of PCs 43,53, 140, 141, 144, 229, 230,259, 261, 276, 357–361spanned by subsets of variables140, 141, 144see also comparisons betweensubspaces

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