CONTENTS xv
7.5 Inference on Multivariate Normal Variances .......... 187
7.6 Fitting Patterned Covariance Matrices ............. 189
7.7 Tests for Multivariate Normality ................ 194
7.8 Exercises ............................. 202
8 Factor Methods 207
8.1 Principal Components Analysis ................. 208
8.2 Example 1: Investment Allocations ............... 210
8.3 Example 2: Kuiper Belt Objects ................ 214
8.4 Example 3: Health Outcomes in US Hospitals ......... 217
8.5 Factor Analysis .......................... 218
8.6 Exercises ............................. 223
9 Multivariable Linear Regression 231
9.1 Univariate Regression ...................... 232
9.2 Multivariable Regression in R .................. 238
9.3 A Large Health Survey ...................... 243
9.4 Exercises ............................. 250
10 Discrimination and Classification 257
10.1 An Introductory Example .................... 257
10.2 Multinomial Logistic Regression ................. 261
10.3 Linear Discriminant Analysis .................. 265
10.4 Support Vector Machine ..................... 273
10.5 Regression Trees ......................... 278
10.6 Exercises ............................. 283
11 Clustering 287
11.1 Hierarchical Clustering ...................... 287
11.2 K-Means Clustering ....................... 295
11.3 Diagnostics, Validation, and Other Methods .......... 301
11.4 Exercises ............................. 308
12 Time Series Models 315
12.1 Introductory Examples and Simple Analyses .......... 315
12.2 Autoregressive Models ...................... 322
12.3 Spectral Decomposition ..................... 333
12.4 Exercises ............................. 336
13 Other Useful Methods 339
13.1 Ranking from Paired Comparisons ............... 339
13.2 Canonical Correlations ...................... 342
13.3 Methods for Extreme Order Statistics ............. 348
13.4 Big Data and Wide Data .................... 354
13.5 Exercises ............................. 356
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