g02kb Example Program Results Number of parameters used = 4 Effective number of parameters (NEP): Ridge Coeff. NEP 0.0000 4.0000 0.0020 3.2634 0.0040 3.1475 0.0060 3.0987 0.0080 3.0709 0.0100 3.0523 0.0120 3.0386 0.0140 3.0278 0.0160 3.0189 0.0180 3.0112 0.0200 3.0045 0.0220 2.9984 0.0240 2.9928 0.0260 2.9876 0.0280 2.9828 0.0300 2.9782 Parameter Estimates (Original scalings) Ridge Coeff. Intercept 1 2 3 0.0000 117.0847 4.3341 -2.8568 -2.1861 0.0020 22.2748 1.4644 -0.4012 -0.6738 0.0040 7.7209 1.0229 -0.0242 -0.4408 0.0060 1.8363 0.8437 0.1282 -0.3460 0.0080 -1.3396 0.7465 0.2105 -0.2944 0.0100 -3.3219 0.6853 0.2618 -0.2619 0.0120 -4.6734 0.6432 0.2968 -0.2393 0.0140 -5.6511 0.6125 0.3222 -0.2228 0.0160 -6.3891 0.5890 0.3413 -0.2100 0.0180 -6.9642 0.5704 0.3562 -0.1999 0.0200 -7.4236 0.5554 0.3681 -0.1916 0.0220 -7.7978 0.5429 0.3779 -0.1847 0.0240 -8.1075 0.5323 0.3859 -0.1788 0.0260 -8.3673 0.5233 0.3926 -0.1737 0.0280 -8.5874 0.5155 0.3984 -0.1693 0.0300 -8.7758 0.5086 0.4033 -0.1653 Variance Inflation Factors Ridge Coeff. 1 2 3 0.0000 708.8429 564.3434 104.6060 0.0020 50.5592 40.4483 8.2797 0.0040 16.9816 13.7247 3.3628 0.0060 8.5033 6.9764 2.1185 0.0080 5.1472 4.3046 1.6238 0.0100 3.4855 2.9813 1.3770 0.0120 2.5434 2.2306 1.2356 0.0140 1.9581 1.7640 1.1463 0.0160 1.5698 1.4541 1.0859 0.0180 1.2990 1.2377 1.0428 0.0200 1.1026 1.0805 1.0105 0.0220 0.9556 0.9627 0.9855 0.0240 0.8427 0.8721 0.9655 0.0260 0.7541 0.8007 0.9491 0.0280 0.6832 0.7435 0.9353 0.0300 0.6257 0.6969 0.9235 Prediction error criterion Ridge Coeff. 1 2 3 4 5 0.0000 8.0368 7.6879 6.1503 7.3804 8.6052 0.0020 7.5464 7.4238 6.2124 7.2261 8.2355 0.0040 7.5575 7.4520 6.2793 7.2675 8.2515 0.0060 7.5656 7.4668 6.3100 7.2876 8.2611 0.0080 7.5701 7.4749 6.3272 7.2987 8.2661 0.0100 7.5723 7.4796 6.3381 7.3053 8.2685 0.0120 7.5732 7.4823 6.3455 7.3095 8.2695 0.0140 7.5734 7.4838 6.3508 7.3122 8.2696 0.0160 7.5731 7.4845 6.3548 7.3140 8.2691 0.0180 7.5724 7.4848 6.3578 7.3151 8.2683 0.0200 7.5715 7.4847 6.3603 7.3158 8.2671 0.0220 7.5705 7.4843 6.3623 7.3161 8.2659 0.0240 7.5694 7.4838 6.3639 7.3162 8.2645 0.0260 7.5682 7.4832 6.3654 7.3162 8.2630 0.0280 7.5669 7.4825 6.3666 7.3161 8.2615 0.0300 7.5657 7.4818 6.3677 7.3159 8.2600 Key: 1 Leave one out cross-validation 2 Generalised cross-validation 3 Unbiased estimate of variance 4 Final prediction error 5 Bayesian information criterion