* Example of Principal Components Regression SAMPLE 1 20 * Data set from Judge, Griffiths, Hill, Lutkepohl and Lee (1985) * Variables X1, X2 and X3 are from Chapter 2, p. 36; * variables X4 and X5 are from Table 22.3, p. 930; and * variable Y1 is from Table 22.4, p. 931. READ X1 X2 X3 X4 X5 Y1 1.0 .693 .693 0.88839 2.05464 16.64 1.0 1.733 .693 2.13713 3.12292 17.77 1.0 .693 1.386 1.16983 2.51224 16.98 1.0 1.733 1.386 1.95618 4.06982 22.40 1.0 .693 1.792 0.79418 3.44152 19.19 1.0 2.340 .693 2.56843 3.99406 22.03 1.0 1.733 1.792 2.05807 3.98592 22.22 1.0 2.340 1.386 2.52166 3.76541 20.85 1.0 2.340 1.792 2.69760 4.54431 22.68 1.0 .693 .693 0.70151 1.62394 16.24 1.0 .693 1.386 1.10589 2.17026 17.85 1.0 1.733 .693 1.74341 3.40309 18.95 1.0 1.733 1.386 1.99744 3.87633 21.12 1.0 .693 1.792 0.85438 3.35228 19.85 1.0 2.340 .693 2.49910 3.72893 21.34 1.0 1.733 1.792 2.13015 3.53070 22.74 1.0 2.340 1.386 2.82119 4.49139 24.36 1.0 2.340 1.792 2.49415 4.90527 24.70 1.0 1.733 1.386 1.89954 3.56241 18.92 1.0 .693 .693 0.85161 1.51745 15.31 * Obtain principal components and some multi-collinearity diagnostics. PC X2 X3 X4 X5 / PCOMP=PC PCINFO=INFO PCOLLIN * Principal components regression OLS Y1 PC:1 PC:2 / PCINFO=INFO PCOMP=PC STOP