Author Index
Aeberhard, S., 31, 134Aebersold, R., 52Afifi, A. A., 297Aggarwal, C. C., 153Aha, D., 425Aharon, M., 463Ahn, J., 60, 156, 157Amari, S.-I., 306, 320–324Amemiya, Y., 237Anderson, J. C., 247Anderson, T. W., 11, 55, 237Angelo, M., 458Ans, B., 306Attias, H., 335
Bach, F. R., 382, 383, 389–396, 398, 400, 409Baik, J., 59Bair, E., 69, 161, 162, 432, 434–436Barbedor, P., 420Bartlett, M. S., 101Basford, K., 184Beirlant, J., 416Bell, A. J., 306, 317Benaych-Georges, F., 471Berger, J. O., 146Berger, R. L., 12, 63, 101, 234, 237, 323,
354, 416Berlinet, A., 386Bernards, R., 50Bibby, J., 11, 75, 263Bickel, J. P., 424Bickel, P. J., 324, 415, 432, 443, 445Bishop, C. M., 62–65, 234, 246, 289, 348,
388Blake, C., 47Blumenstock, J. E, 448Borg, I., 248Borga, M., 114, 169Boscolo, R., 419Breiman, L., 304Bruckstein, A., 463Bueno, R., 448Buja, A., 282, 285, 361
Cabrera, J., 361Cadima, J., 449Calinski, R. B., 198, 217Candes, E. J., 422, 463Cao, X.-R., 317Cardoso, J.-F., 306, 311–314, 316–324, 326, 329,
334, 335, 365Carroll, J. D., 274Casella, G., 12, 63, 101, 234, 237, 323,
354, 416Chaney, E. L., 336Chaudhuri, P., 199Chen, A., 324, 415Chen, J. Z., 336, 338, 339, 429–431Chen, L., 282, 285Chervonenkis, A., 382, 383Chi, Y.-Y., 60Choi, S., 306, 322Cichocki, A., 306, 322Cloutier, I., 160Comon, P., 297, 306, 308, 311, 313,
314, 317–319, 365, 476Cook, D., 8, 361Cook, R. D., 342Coomans, D., 31, 134Cooper, M. C., 217Corena, P., 204Cormack, R. M., 178Cover, T. M., 150, 299, 316Cowling, A., 199Cox, D. R., 321Cox, M. A. A., 248, 258, 265, 273Cox, T. F., 248, 258, 265, 273Cristianini, N., 114, 148, 155, 156, 383,
386Critchley, F., 382, 403, 404, 406–410, 412
Dai, H., 50Davies, C., 204Davies, P. I., 332Day, C., 50, 277De Bie, T., 114de Silva, V., 282, 284, 285de Vel, O., 31, 134
493
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494 Author Index
Degenhardt, L., 50, 277Devroye, L., 117, 132, 148, 150Diaconis, P., 342, 350, 351Domeniconi, C., 153Domingos, P., 443Donoho, D. L., 76, 306, 422, 463Dryden, I. L., 273Dudewicz, E. J., 416Dudley, R. M., 362, 414Dudoit, S., 443Duong, T., 199, 360Dumbgen, L., 382, 403, 404, 406–410, 412
Elad, M., 422, 463Elisseeff, A., 424Eriksson, J., 324, 382, 393, 403–410,
412–414Eslava, G., 361
Fan, J., 161, 348, 432, 443, 445–448Fan, Y., 161, 348, 432, 443, 445–448Figueiredo, M. A. T., 216Fisher III, J. W., 382, 413, 416Fisher, N. I., 199, 217Fisher, R. A., 3, 117, 120, 121, 216Fix, E., 149Flury, B., 28Fraley, C., 216Frank, E., 304, 424Freedman, D., 342, 350, 351Fridlyand, J., 443Friedland, S., 459Friedman, J., 66, 67, 95, 118, 148, 152, 155, 156,
170, 304, 349–351, 354, 355, 358–364, 366,367, 375–378
Friend, S. H., 50Fukunaga, K., 153
Gasser, Th., 450Gentle, J. E., 14Gerald, W., 458Gerbing, D. W., 247Ghahramani, Z., 198, 216Gilmour, S., 50, 80, 277, 427, 428Girolami, M., 306, 317Givan, A. L., 25, 397Gokcay, E., 216Golub, T., 458Gordon, G. J., 448Gower, J. C., 61, 181, 248, 249, 251, 252, 271,
279–283, 291Graef, J., 285Greenacre, M. J., 274Groenen, P. J. F., 248Gullans, S. R., 448Gunopulos, D., 153Gustafsson, J. O. R., 52, 212, 215
Guyon, I., 424Gyorfi, L., 117, 132, 148, 150, 416
Hall, P., 48, 335, 339–342, 350, 354, 355, 358,373–376, 378
Hand, D. J., 117, 148, 184Harabasz, J., 198, 217Harrison, D., 87Hart, A. A. M., 50Hart, P., 150Hartigan, J., 178Hartigan, J. A., 217Harville, D. A., 14Hastie, T., 66, 67, 69, 95, 118, 148, 149,
152, 153, 155, 156, 161, 162, 185, 199,217–220, 257, 324, 420, 432, 434–436,452–456, 458–460
Haueisen, J., 306Hazelton, M. L., 360He, Y. D., 50Helland, I. S., 109–112Higham, N.J., 332Hinkley, D. V., 321Hinneburg, A., 153Hodges, J., 149Hoffmann, P., 52Hotelling, H., 3, 18, 71Householder, A. S., 248, 261Hsiao, L., 448Huang, J., 458–460Huang, J. Z., 458Huber, P. J., 350, 351, 354Hyvarinen, A., 306, 318, 320, 326, 329, 334, 335,
342, 365, 366, 400Herault, J., 306
Inselberg, A., 6Ivanova, G., 306Izenman, A. J., 285
Jain, A. K., 216Jeffers, J., 452Jensen, R. V., 448Jing, J., 199–202, 204, 288John, S., 60Johnstone, I. M., 48, 58–60, 261, 422, 461–465,
471, 475Jolliffe, I. T., 449–453, 456Jones, M. C., 34, 199, 349–352, 354, 357–361,
363, 364, 366, 379, 417Jordan, M. I., 382, 383, 389–396, 398, 400, 409Joshi, S., 336Jung, S., 48, 59–61, 261, 271, 422, 461, 462,
465–469, 471, 475Jutten, C., 306Joreskog, K. G., 247
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Author Index 495
Kaiser, H. F., 226Karhunen, J., 306, 320, 335, 366Keim, D. A., 153Kelleher, A. D., 202, 204, 288Kent, J., 11, 75, 263Kerkhoven, R. M.., 50Kibler, D., 425Klemm, M., 306Knutsson, H., 114, 169Koch, I., 50, 75, 80, 108, 161, 199–202, 204, 212,
277, 288, 336, 338, 339, 344–346, 348,423–436, 438, 440, 443, 445, 447, 448
Koivnen, V., 324, 382, 393, 413, 414Kolassa, J., 299Kruskal, J. B., 248, 263, 268, 350Krzanowski, W. J., 217, 279–281, 283Kshirsagar, A. M., 101Kullback, S., 374Kusano, N., 199
Ladd, C., 458Lai, Y. T., 217Landelius, T., 114, 169Lander, E., 458Langford, J. C., 285Latulippe, E., 458Lawley, D. N., 237Lawrence, N., 388Learned-Miller, E. G., 382, 413, 416Lee, E. R., 461Lee, J. A., 285Lee, S., 471Lee, S.-Y., 306, 322Lee, T.-W., 306, 317Lee, Y. K., 461Lemieux, C., 160Leng, C., 461Levina, E., 424, 432, 443, 445Li, K.-C., 335, 339–342Linsley, P. S., 50Liu, R.-W., 317Lu, A. Y., 261, 461–465, 471, 475Loda, M., 458Lugosi, G., 117, 132, 148, 150
Ma, Z., 461, 465, 471Malkovich, J. F., 297Mallat, S., 465Mammen, E., 199, 217Mann, M., 52Mao, M., 50Mardia, K. V., 11, 75, 263, 273Marriott, F. H. C., 361Marron, J. S., 32, 34, 48, 59–61, 156, 157, 199,
212, 217, 261, 271, 336, 338, 339, 422,429–431, 461, 462, 465–471, 473, 475
Marton, M. J., 50Marcenko, V. A., 58
Mathes, H., 246Maxwell, A. E., 237McColl, S. R., 52McCullagh, P., 153, 299, 319McLachlan, G, 184, 216Merz, C., 47Mesirov, J., 458Messick, S., 273Meulman, J. J., 251, 254, 257, 268,
274Miller, A., 157Milligan, G. W., 217Minka, T. P., 64Minotte, M. C., 199, 217Moodie, Z., 25, 397Motomura, Y., 324Mueller, K. M., 60Mukheriee, S., 458Muller, K.-R., 285, 383, 385, 386
Nadakuditi, R., 471Nadler, B., 463, 471Naito, K., 108, 161, 199–201, 344–346,
348, 432–436, 438, 440, 443, 445,447, 448
Nason, G., 363, 364Neeman, A., 48Nelder, J. A., 153
Oehler, M. K., 52Ogasawara, H., 246Oja, E., 306, 320, 335, 366Oja, H., 382, 403–410, 412Olshen, R. A., 304
Pan, H., 419Park, B. U., 461Park, H.-M., 306, 322Partridge, E., 28Pastur, L. A.., 58Paul, D., 59, 69, 161, 162, 432, 434–436,
463, 471Pazzani, M., 443Pearson, K., 3, 18Peel, D., 184, 216Peng, J., 153Peterse, H. L., 50Petersen, K. B., 335Pizer, S. M., 336Poggio, T., 458Prasad, M., 423–426Principe, J. C., 216Pryce, J. D., 87
Qui, X., 153Quist, M., 282–284
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496 Author Index
Raftery, A., 216Rai, C. S., 331Ramaswamy, S., 448, 458Ramos, E., 76Ramsay, J. O., 269Rao, C.R., 237Reich, M., 458Richards, W. G., 448Richardson, M. W., 248Riedwyl, H., 28Rifkin, R., 458Ripley, B. D., 148, 379Roberts, C., 50Romberg, J., 422Rosipal, R., 109, 110, 112, 114Ross, D., 223Rossini, A., 25, 397Rousson, V., 450Roweis, S. T., 198, 216, 285Roychowdhury, V. P., 419Rubin, H., 237Rubinfeld, D. L., 87Rudin, W., 387Ruszkiewicz, A., 52
Sagae, M., 199Samarov, A., 382, 413, 417–419Saul, L. K., 285Schneeweiss, H., 246Schoenberg, I. J., 261Schott, J. R., 200Schreiber, G. J., 50Schroeder, A., 350, 376–378Scholkopf, B., 148, 155, 156, 285, 383, 385, 386Scott, D. W., 34, 199, 360, 417Searle, S. R., 14Sejnowski, T. J., 306, 317Sen, A., 422, 461, 465, 468, 469, 471, 475Serfling, R. J., 200Shashua, A., 450Shawe-Taylor, J., 148, 155, 156, 383, 386Shen, D., 422, 461, 465, 470, 471, 473, 475Shen, H., 422, 458–461, 465, 470, 471, 473, 475Shepard, R. N., 248, 263Short, R. D., 153Sibson, R., 349–352, 354, 357–361, 363, 364,
366Silverman, B. W., 199, 217, 269Silverstein, J. W., 59Singh, Y., 331Sirkia, S., 382, 403–410, 412Smola, A., 148, 155, 156, 285, 383, 385, 386Sowmya, A., 423–426Speed, T. P., 443Spence, I., 285Starck, J.-L., 463Stone, J., 304Strang, G., 14Stuetzle, W., 350, 376–378
Sugarbaker, D. J., 448Swayne, D., 8
Tamatani, M., 432, 438, 440, 443, 445, 447,448
Tamayo, P., 458Tanguay, J.-F., 160Tao, T., 422Tenenbaum. J. B., 282, 284, 285Thomas, J. A., 299, 316Thomas, M., 204Thomas-Agnan, C., 386Tibshirani, R., 66, 67, 69, 95, 118, 148, 149, 152,
153, 155, 156, 161, 162, 185, 198, 199, 215,217–220, 222, 257, 324, 420, 432, 434–436,450, 452–456, 458–460
Tipping, M. E., 62–65, 234, 246, 289, 348,388
Todd, M., 157Torgerson, W. S., 248, 254Torokhti, A., 459Tracy, C. A., 58, 59Trejo, L. J., 109, 110, 112Trendafilov, N. T., 450–453, 456Trosset, M. W., 254, 261–263, 268Tsybakov, A., 382, 413, 417–419Tucker, L. R., 273Tukey, J. W., 350, 354, 363, 376Tyler, D. E., 382, 403, 404, 406–410,
412
Uddin, M., 450–453, 456
van de Vijver, M. J., 50van der Kooy, K., 50van der Meulen, E.C., 416van’t Veer, L. J., 50Vapnik, V., 156, 382, 383, 386Vasicek, O., 416Venables, W. N., 379Verleysen, M., 285Vines, S. K., 450Vlassis, N., 324von Storch, H., 100
Walter, G., 185, 199, 217–220, 222Wan, J., 25, 397Wand, M. P., 34, 199, 358, 379, 417Wang, H., 461Wegman, E., 8Widom, H., 58, 59Williams, R. H., 223Winther, O., 335Wish, M., 248Witten, D. M., 198, 215, 458–460Witten, I. H, 304, 424Witteveen, A. T., 50
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Author Index 497
Wold, H., 109Wright, F. A., 471Wu, L., 153Wunsch, D., 184
Xu, R., 184
Yeang, C., 458Yeredor, A., 382, 413, 414Yin, X., 342
Yona, G., 282–284Young, G., 248, 261
Zass, R., 450Zaunders, J. , 202, 204, 288Zhu, H., 461, 465, 470, 471Zimmerman, D. W., 223Zou, F., 471Zou, H., 257, 452–456, 458Zumbo, B. D., 223Zwiers, F. W., 100
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Subject Index
χ2 distance, 278χ2 distribution, 11, 278χ2 statistic, 278k-factor model, 224
sample, 227k-means clustering, 192m-spacing estimate, 416p-ranked vector, 160F-correlation, 392HDLSS consistent, 60, 444LASSO estimator, 450
affineequivariant, 403proportional, 403
asymptoticdistribution, 56normality, 55theory, Gaussian data, 4
Bayes’ rule, 145Bernoulli trial, 154binary data, 213biplot, 231
canonicalcorrelation matrix, 73matrix of correlations, 77projections, 74variables, 74variate vector, 74variates, 74, 78variates data, 78
canonical correlationdata, 78matrix, 73, 390matrix DA-adjusted, 439projections, 74, 78regression, 108score, 74, 78variables, 74
CC matrix See also canonical correlationmatrix, 73
central moment, 297sample, 298
characteristic function, 414sample, 414second, 415
class, 118average sample class mean,
123sample mean, 123
classification, 117error, 132
classifier, 120cluster, 192
k arrangement, 192centroid, 185, 192image, 213map, 213optimal arrangement, 192PC data k arrangement, 208tree, 187within variability, 192
clusteringk-means, 192agglomerative, 186divisive, 186hierarchical, 186
co-membership matrix, 219coefficient of determination
multivariate, 73sample, 77
collinearity, 47communality, 225concentration idea, 463confidence interval, 56
approximate, 56configuration, 251
distance, 251contingency table, 274correlatedness, 315cost factor, 132covariance matrix, 9
between, 72pooled, 136, 141regularised, 155sample, 10
498
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Subject Index 499
spatial sign, 404spiked, 59
Cramer’s condition, 443cross-validation, 303
error, 134, 303m-fold, 303n-fold, 134
cumulant, 299generating function, 415
datafuntional, 48observed, 250scaled, scaling, 44source, 308sphered, sphering, 44standardised, 44whitened or white, 311
decisionboundary, 130function, 120, 130
decision function, preferential, 139decision rule, preferential, 145dendrogram, 187derived (discriminant) rule, 158dimension
most non-Gaussian, 346selector, 346
direction (vector), 17direction of a vector, 296discriminant
direction, 122Fisher’s rule, 124function, 121region, 130rule, 117, 120sample function, 123sample direction, 124
discriminant rule, 117(normal) quadratic, 140, 141Bayesian, 145derived, 158k-nearest neighbour or k-NN, 150logistic regression, 154normal, 128regularised, 155
disparity, 264dissimilarity, 178, 250distance, 177
Bhattacharyya, 178Canberra, 178Chebychev, 178city block, 178correlation, 178cosine, 178discriminant adaptive nearest neighbour
(DANN), 153Euclidean, 177Mahalanobis, 177
max, 178Minkowski, 178Pearson, 178profile, 278weighted p-, 178weighted Euclidean, 178
distance-weighted discrimination, 157distribution
F, 12Poisson, 141, 142spherical, 296Wishart, 469
distribution function, 354empirical, 362
eigenvaluedistinct, 15generalised, 114, 122, 394
eigenvectorleft, 17right, 17
embedding, 180, 251ensemble learning, 304entropy, 300
differential, 300relative, 301
error probability, 135expected value, 9
F distribution, 12factor, 224
k model, 224common, 224, 305loadings, 224rotation, 234scores, 225, 239specific, 224
factor scores, 225, 239Bartlett, 241CC, 242ML, 240PC, 240regression, 243Thompson, 241
FAIR, 443feature, 180
correlation, 391covariance operator, 386data, 384extraction, 181kernel, 384map, 180, 384score, 386selection, 160, 181space, 384vector, 180
features annealed independence rule (FAIR), 443Fisher’s (linear) rule, 122
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500 Subject Index
functioncharacteristic, 414contrast, 313distribution, 354estimating, 322estimating learning rule, 322score, 321
functional data, 48
gap statistic, 218Gaussian, 11
Hotelling’s T 2, 11likelihood function, 12multivariate, 11probability density function, 12random field, 345sub, 331super, 331
Gram matrix, 387
HDLSS consistent, 444high-dimensional
HDD, 48HDLSS, 48
homogeneity analysis, 274hyperplane, 130
IC See also independent component(s), 325ICA, orthogonal approach, 312idempotent, 37independence property, 403independent component
almost solution, 313data, 325direction, 325model, 307, 308projection, 325score, 325solution, 312vector, 325white model, 312
independent, as possible, 313inner product, 179, 384input, 118interesting
direction, 296projection, 296
k-nearest neighbour rule, 150k-nearest neighbourhood, 150Kendall’s τ matrix, 404kernel, 384
generalised variance, 396matrix, 387reproducing Hilbert space, 386reproducing property, 384
kernel density estimator, leave-one-out, 358
Kronecker delta function, 17Kullback-Leibler
divergence or distance, 300Kullback-Leibler divergence, 180kurtosis, 297
sample, 298
label, 119labelled random vector, 119vector-valued, 119
LASSO estimator, 450learner, 120, 304least squares estimator, 66leave-one-out
error, 133method, 133training set, 133
likelihood function, 127linkage, 186
average, 186centroid, 186complete, 186single, 186
loadings, 20loss function, 147
machine learning, 118, 184margin, 156matrix
Gram, 387Kendall’s τ , 404kernel, 387mixing, 307, 308of group means, 281orthogonal, 15permutation, 308Q- and R-, 181r -orthogonal, 15, 181scatter, 403separating or unmixing, 307similar, 14whitening, 311
maximum likelihood estimator, 12mean, 9
sample, 10measure
dissimilarity, 178similarity, 179, 384
metric, 177Manhattan, 178
misclassificationprobability of, 135
misclassified, 124misclassify, 120ML factor scores, 240mode estimation, 199multicollinearity, 47mutual information, 300
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Subject Index 501
naive Bayes, 441canonical correlation, 441rule, 424
negentropy, 300neural networks, 148non-Gaussian, non-Gaussianity, 315norm, 177
�1, �2, �p , 176�2, 177Frobenius, 176sup, 176trace, 39weighted �p, 178
observed data, 250order statistic, 416orthogonal proportional, 403output, 118
p-whitened data, 336Painleve II differential equation, 58pairwise observations, 250partial least squares (regression), 109pattern recognition, 148PC See also principal component(s), 20plot
horizontal parallel coordinate, 7parallel coordinate, 6, 43, 134scatterplot, 4, 5score, 30scree, 27vertical parallel coordinate, 6
posterior error, 445worst case, 445
predictionerror loss, 220strength, 220
predictor, derived, 67principal component
data, 23discriminant analysis, 158factor scores, 240projection, 20, 23score, 20, 23score plot, 30sparse, 451, 455supervised, 161vector, 20
principal coordinate analysis, 252principal coordinates, 252probability
conditional, 144posterior, 144posterior of misclassification, 445prior, 144
Procrustes analysis, 273Procrustes rotation, 271profile, 278
distance, 278equivalent, 278
projection(vector), 17index, 349interesting, 296pursuit, 306
projection index, 349, 351bivariate, 359cumulant, 357deviations from the uniform, 353difference from the Gaussian, 353entropy, 353Fisher information, 353ratio with the Gaussian, 353regression, 379
projection pursuit, 306augmenting function, 377density estimate, 377
projective approximation, 380proximity, 180
Q-matrix, 181qq-plot, 342
R-matrix, 181random variable, 9random vector
components, entries or variables, 9labelled, 119scaled, scaling, 44sphered, sphering, 44standardised, 44
rank k approximation, 458rank orders, 263ranked dissimilarities, 263ranking vector, 160, 433rankings, 263Rayleigh quotient, 114, 122regression factor scores, 243risk
Bayes, 147function, 147
rotational twin, 340rule, 120
Fisher’s (discriminant), 122naive Bayes, 424
scalar product, 179scaled, scaling See also random vector and data, 44scaling, three-way, 273scatter functional, 403scatter matrix, 403score plot, 30SCoTLASS direction, 451sign rule
PC1, 210
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502 Subject Index
signal, 307, 308mixed, 307, 308whitened or white, 311
similarity, 179, 384singular value, 16
decomposition, 16skewness, 297
sample, 298soft thresholding, 459source
(vector), 307data, 308unknown, 62
sparse, 449sparse principal component, 455
criterion, elastic net, 455SCoTLASS, 451
sparsity, 449, 457spatially white, 311spectral decomposition, 15, 16, 37sphered, sphering See also random vector and
data, 44sphericity, 60spikiness, 60sstress, 258
non-metric, 264statistical learning, 118, 184strain, 254stress, 251
classical, 251metric, 258non-metric, 264Sammon, 258
structure removal, 362sup norm, 176supervised learning, 118, 133
support vector machine, 383support vector machines, 148
testing, 118three-way scaling, 273total variance
cumulative contribution, 27proportion, 27
trace, 14norm, 39
Tracy Widom law, 58training, 118
uncorrelated, 9unsupervised learning, 118, 184
variabilitybetween-class, 121between-class sample, 123between-cluster, 216within-class, 121within-class sample, 123within-cluster, 192
variableranking, 160selection, 160
variablesderived, 67latent, 62, 69, 305latent or hidden, 224
varimax criterion, 226
Wishart, 11Wishart distribution, 469
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Data Index
abalone (d = 8,n = 4,177)2 PCA, 46, 64, 68, 1663 CCA, 1126 CA, 1917 FA, 239
assessment marks (d = 6,n = 23)8 MDS, 276
athletes (d = 12,n = 202)8 MDS, 255, 26011 PP, 370
Boston housing (d = 14,n = 506)3 CCA, 87
breast cancer (d = 30,n = 569)2 PCA, 29, 32, 43, 46, 65, 1664 DA, 137, 151, 1626 CA, 196, 2097 FA, 239
breast tumour (d = 4,751,24,481,n = 78)2 PCA, 508 MDS, 27013 FS-PCA, 436
car (d = 5,n = 392)3 CCA, 75, 797 FA, 228, 234
cereal (d = 11,n = 77)8 MDS, 264
Dow Jones returns (d = 30,n = 2,528)2 PCA, 29, 32, 1666 CA, 2117 FA, 232
exam grades (d = 5,n = 120)7 FA, 238, 244
HIV flow cytometry (d = 5,n = 10,000)1 MDD, 52 PCA, 24, 41, 1656 CA, 22012 K&MICA, 397
HRCT emphysema (d = 21,n = 262,144)13 FS-PCA, 423, 425
illicit drug market (d = 66,n = 17)1 MDD, 72 PCA, 493 CCA, 80, 84, 89, 98, 1066 CA, 2107 FA, 2308 MDS, 259, 27710 ICA, 329, 34312 K&MICA, 38813 FS-PCA, 427
income (d = 9,n = 1,000)2 PCA, 1663 CCA, 95, 102
iris (d = 4,n = 150)1 MDD, 5, 64 DA, 124, 1506 CA, 187, 19310 ICA, 327
(data bank of) kidneys (d = 264,n = 36)10 ICA, 33613 FS-PCA, 429, 430
lung cancer (d = 12,553,n = 181)13 FS-PCA, 448
ovarian cancer proteomics (d = 1,331,n = 14,053)2 PCA, 526 CA, 2138 MDS, 278, 281
PBMC flow cytometry (d = 10,n = 709,086)6 CA, 202
pitprops (d = 14,n = 180)13 FS-PCA, 451, 456
simulated data (d = 2− 50,n = 100–10,000)2 PCA, 24, 35, 165
503
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504 Data Index
4 DA, 125, 128, 130, 141, 1456 CA, 195, 2089 NG, 29610 ICA, 342, 34611 PP, 367
sound tracks (d = 2,n = 24,000)10 ICA, 308, 329
South Australian grapevine(d = 19,n = 2,062)
6 CA, 204
Swiss bank notes (d = 6,n = 200)2 PCA, 28, 30
ten cities (n = 10)8 MDS, 250, 253, 267
wine recognition (d = 13,n = 178)2 PCA, 314 DA, 134, 13912 K&MICA, 399, 409
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