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| Haerdle W., Simar L. — Applied multivariate statistical analysis |
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| Предметный указатель |
Admissible 329
Agglomerative techniques 308
Allocation rules 323
Andrews' curves 39
Angle between two vectors 75
anova 103
ANOVA - simple analysis of variace 103
Bayes discriminant rule 328
Bernoulli distribution 143
Bernoulli distributions 143
Best line 221
Binary structure 303
Biplots 356
Bootstrap 148
Bootstrap sample 150
Boston housing 44 112 209 259 293 316 337
Boxplot 15
Boxplot construction 17
Canonical correlation 361
Canonical correlation analysis 361
Canonical correlation coefficient 363
Canonical correlation variable 363
Canonical correlation vector 363
Centering matrix 93
Central Limit Theorem (CLT) 143 145
Centroid 312
Characteristic functions 125 131
Classic blue pullovers 84
Cluster algorithms 308
Cluster analysis 301
Cochran theorem 163
Coefficient of determination 98 109
Coefficient of determination, corrected 109
Column space 77 221
Common factors 277
Common principal components 256
Communality 278
Complete linkage 311
Computationally intensive techniques 421
Concentration ellipsoid 138
Conditional approximations 160
Conditional covariance 433
Conditional density 121
Conditional distribution 157
Conditional expectation 127 432 433
Conditional pdf 120
Confidence interval 145
Confussion matrix 332
Conjoint measurement analysis 393
Contingency table 341
contrast 195
Convex hull 423
Copula 122
Correlation 86
Correlation, multiple 160
Correspondence analysis 341
Covariance 82
Covariance matrix decomposition 234
Covariance matrix properties 126
CPCA 256
Cramer — Rao 179
Cramer — Rao lower bound 178
Cramer — Wold 132
Cumulant 133
Cumulative distribution function (cdf) 120
Curse of dimensionality 431
Data depth 423
Data sets, XFGvolsurf01 257
Data sets, XFGvolsurf02 257
Data sets, XFGvolsurf03 257
Degrees of freedom 105
Dendrogram 310
Density estimates 22
Density functions 120
derivatives 68
Determinant 59
Diagonal matrix 59
Dice 304
Discriminant analysis 323
Discriminant rule 324
Discrimination rules in practice 331
Dissimilarity of cars 376
Distance matrix 379
Distance measures 305
Distance, d 71
Distance, Euclidean 71
Distance, iso-distance curves 71
distribution 120
Draft man's plot 32
Duality relations 227
Duality theorem 382
Effective dimension reduction directions 431 433
Effective dimension reduction space 431
Efficient portfolio 408
Eigenvalues 61
Eigenvectors 61
Elliptical distribution 167
Elliptically symmetric distribution 431
Estimation 173
Existence of a riskless asset 412
Expected cost of misclassification 325
Explained variation 98
Exploratory projection pursuit 425
Extremes 17
F-spread 16
F-test 106
Faces 34
Factor analysis 275
Factor analysis model 275
Factor model 282
Factor score 291
Factor scores 291
Factorial axis 223
Factorial method 250
Factorial representation 229 231
Factorial variable 223 230
Factors 221
Farthest Neighbor 311
Fisher information 180
Fisher information matrix 178 179
Fisher's linear discrimination function 333
Five-number summary 15
Flury faces 35
Fourths 15
French food expenditure 253
Full model 105
G-inverse 60
G-inverse, non-uniqueness 64
General multinormal distribution 165
Gradient 68
Group-building algorithm 302
hessian 68
Hierarchical algorithm 308
Histograms 22
Hotelling redistribution 165
Idempotent matrix 59
Identity matrix 59
Independence copula 123
Independent 87 121
Inertia 229 231
Information matrix 179
Interpretation of the factors 278
| Interpretation of the principal components 241
Invariance of scale 279
Inverse 60
Inverse regression 431 433
Jaccard 304
Jacobian 135
Jordan decomposition 63 64
Kernel densities 25
Kernel estimator 25
Kulczynski 304
Likelihood function 174
Likelihood ratio test 184
Limit theorems 142
Linear discriminant analysis 327
Linear regression 95
Linear transformation 94
Link function 431
Loadings 277 278
Loadings, non-uniqueness 280
Log-likelihood function 174
Mahalanobis distance 327
Mahalanobis transformation 95 137 138
Marginal densities 121
Marketing strategies 104
Maximum likelihood discriminant rule 324
Maximum likelihood estimator 174
MDS direction 376
Mean-variance 407 408
Median 15 422
Metric methods 377
Moments 125
Multidimentional scaling 373
Multinormal 139 155
Multinormal distribution 137
Multivariate distributions 119
Multivariate median 423
Multivariate t-distribution 168
Nearest neighbor 311
Non-metric solution 400
Nonexistence of a riskless asset 410
Nonhomogeneous 94
Nonmetric methods of MDS 377
Norm of a vector 74
Normal distribution 175
Normalized principal components (NPCs) 249
Null space 77
Order statistics 15
Orthogonal complement 78
Orthogonal matrix 59
Orthonormed 223
Outliers 13
Outside bars 16
Parallel coordinates plots 42
Parallel profiles 205
Partitioned covariance matrix 156
Partitioned matrices 68
PAV algorithm 384 405
Pool-adjacent violators algorithm 384 405
Portfolio analysis 407
Portfolio choice 407
Positive definite 65
Positive definiteness 67
Positive or negative dependence 34
Positive semidefinite 65 93
Principal axes 73
Principal component method 286
Principal components 237
Principal components analysis (PCA) 233 432 435
Principal components in practice 238
Principal components technique 238
Principal components transformation 234 237
Principal factors 285
Profile analysis 205
Profile method 396
Projection matrix 77
Projection pursuit 425
Projection pursuit regression 428
Projection vector 431
Proximity between objects 302
Proximity measure 302
Quadratic discriminant analysis 330
Quadratic form 65
Quadratic forms 65
Quality of the representations 252
Randomized discriminant rule 329
Rank 58
Reduced model 105
Rotation 289
Rotations 76
Row space 221
Russel and Rao (RR) 304
Sampling distributions 142
Scatterplot matrix 31
Scatterplots 30
Separation line 31
Similarity of objects 303
Simple Matching 304
Single linkage 311
Single matching 305
Singular normal distribution 140
Singular value decomposition (SVD) 64 228
Sliced inverse regression 431 435
Sliced inverse regression II 433 434 436 437
Sliced inverse regression II, algorithm 434
Sliced inverse regression, algorithm 432
Solution, nonmetric 403
Specific factors 277
Specific variance 278
Spectral decompositions 63
Spherical distribution 167
Standardized linear combinations (SLC) 234
Statistics 142
Stimulus 395
Student's t-distribution 96
Sum of squares 105
Summary statistics 92
Swiss bank data 14
Symmetric matrix 59
t-test 96
Tanimoto 304
Testing 183
The CAPM 417
Total variation 98
Trace 58
Trade-off analysis 396
Transformations 135
TRANSPOSE 60
Two factor method 396
Unbiased estimator 179
Uncorrelated factors 277
Unexplained variation 98
Unit vector 74
Upper triangular matrix 59
Variance explained by PCs 247
Varimax criterion 290
Varimax method 289
Varimax rotation method 289
Ward clustering 312
Wishart distribution 162 164
XFGvolsurf02 data 257
XFGvolsurf03 data 257
XFGvolsurf0l data 257
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