Page 500 - Jolliffe I. Principal Component Analysis

of correlations between variables
and components 404
for outliers 236, 238, 239, 241,
of data 63, 78–110, 130, 200, for normality 402 Index 465
367, 368
201, 212, 214, 215, 217–219, for periodicities 304, 314
235–236, 242, 244–247, 338, for specified PC coefficients 53,
341, 353, 367 293, 394
of intrinsically high-dimensional for specified PC variances 53,
data 107–110 114, 394
group structure 80, 145, 299, 387, see also likelihood ratio test,
2
398 minimum χ test
see also cluster analysis,
discriminant analysis ill-conditioning 390
growing scale PCA 334 see also multicollinearity
growth curves 328, 330, 331 image processing 56, 346, 395, 401
eigenimages 346
Hilbert EOF analysis see complex Imbrie’s Q-mode method 390
PCA imputation of missing values 363,
Hilbert transforms 310, 329, 369 366
history of PCs 6–9 independent component analysis
2
Hotelling’s T 205, 356, 367, 368 (ICA) 373, 395, 396
household formation 195–198, indicator matrices 343
245–247 inference for PCs see estimation,
Householder transformation 410, hypothesis testing, interval
412 estimation
how many factors? 116, 126, 130, influence function
131, 159, 162 additivity 251
how many PCs? 43, 53, 54, 63, 78, deleted empirical influence
111–137, 159, 222, 230, 238, function 251
253, 261, 271, 327, 332, 333, empirical influence function 251
338, 385, 387, 395 for PC coefficients and
see also parallel analysis, rules variances 253–259
for selecting PCs local 262
hypothesis testing sample influence function 249,
for common PCs 356–360 250, 252
for cumulative proportion of for PC coefficients and
total variance 55 variances 253–259
for equality of multivariate for regression coefficients 249
means 205 standardized influence matrix
for equality of PC variances 240
53–55, 118, 119, 128, 131, theoretical influence function
132, 136, 276, 394 for correlation coefficients 250
for equivalence of subspaces 360 for PC coefficients and
for Hilbert EOFs 311 variances 249–251, 253, 263
for linear trend in PC variances for robust PCA 267
120, 356 for subspaces 252–254