Output of BOXMEYER from input file FF84Ex2.txt HEADING LINE in FF84Ex2.txt: 2_IV^{8-4} design (Paint abrasion resistance): Table 6.17 in Box-Hunter-Hunter Values of variables: Nrows=16 Ncols=8 Nvars=8 Pi=0.25 Gamma=2.5 Alpha=2 Data in FF84Ex2.txt: Rownum, Design matrix, Response variable Row A B C D E F G H AbrasRes 1. -1 -1 -1 -1 -1 -1 -1 -1 6.3 2. 1 -1 -1 -1 1 1 1 -1 6.1 3. -1 1 -1 -1 1 1 -1 1 5.5 4. 1 1 -1 -1 -1 -1 1 1 2.1 5. -1 -1 1 -1 1 -1 1 1 6.9 6. 1 -1 1 -1 -1 1 -1 1 5.1 7. -1 1 1 -1 -1 1 1 -1 6.4 8. 1 1 1 -1 1 -1 -1 -1 2.5 9. -1 -1 -1 1 -1 1 1 1 8.2 10. 1 -1 -1 1 1 -1 -1 1 3.1 11. -1 1 -1 1 1 -1 1 -1 4.3 12. 1 1 -1 1 -1 1 -1 -1 3.2 13. -1 -1 1 1 1 1 -1 -1 7.1 14. 1 -1 1 1 -1 -1 1 -1 3.4 15. -1 1 1 1 -1 -1 -1 1 3 16. 1 1 1 1 1 1 1 1 2.8 Factor labels: ABCDEFGH Factors analyzed: ABCDEFGH Models and submodels (n=92): A B C D E F G H AB AC AD AE AF AG AH BC BD BE BF BG BH CD CE CF CG CH DE DF DG DH EF EG EH FG FH GH ABC ABD ABE ABF ABG ABH ACD ACE ACF ACG ACH ADE ADF ADG ADH AEF AEG AEH AFG AFH AGH BCD BCE BCF BCG BCH BDE BDF BDG BDH BEF BEG BEH BFG BFH BGH CDE CDF CDG CDH CEF CEG CEH CFG CFH CGH DEF DEG DEH DFG DFH DGH EFG EFH EGH FGH Best 5 for each model size: Model AdjRsq Rmse Fstat* Likelihood Rmsec BPostProb ----------------------------------------------------------------------- A 0.38039 1.5179 10.2089 5.1e-013 1.5234 0.065 B 0.25146 1.6684 6.0390 1.1e-013 1.6720 0.016 F 0.12526 1.8036 3.1480 3.2e-014 1.8056 0.005 D -0.03104 1.9581 0.5484 8.6e-015 1.9585 0.0015 G -0.04819 1.9743 0.3104 7.5e-015 1.9745 0.0013 ------------------------------------------------------------------- AB 0.66061 1.1234 10.7323 2.1e-010 1.1382 0.054 AF 0.50710 1.3539 6.1441 1.1e-011 1.3641 0.0035 BF 0.35707 1.5462 3.7769 1.3e-012 1.5534 0.00051 AD 0.32514 1.5842 3.4089 8.8e-013 1.5908 0.00035 AG 0.32043 1.5897 3.3576 8.3e-013 1.5963 0.00034 -------------------------------------------------------------------- ABD 0.90790 0.5852 22.1230 0.00019 0.6389 0.21 ABF 0.90790 0.5852 22.1230 0.00019 0.6389 0.21 BDF 0.90790 0.5852 22.1230 0.00019 0.6389 0.21 ADF 0.90790 0.5852 22.1230 0.00019 0.6389 0.21 AGH 0.57545 1.2565 3.9045 9.2e-010 1.2776 6.5e-006 All models sorted together by Fstat (best 15 out of 92): Model AdjRsq Rmse Fstat* Likelihood Rmsec BPostProb ----------------------------------------------------------------------- ABD 0.90790 0.5852 22.1230 0.00019 0.6389 0.21 ABF 0.90790 0.5852 22.1230 0.00019 0.6389 0.21 BDF 0.90790 0.5852 22.1230 0.00019 0.6389 0.21 ADF 0.90790 0.5852 22.1230 0.00019 0.6389 0.21 AB 0.66061 1.1234 10.7323 2.1e-010 1.1382 0.054 A 0.38039 1.5179 10.2089 5.1e-013 1.5234 0.065 AF 0.50710 1.3539 6.1441 1.1e-011 1.3641 0.0035 B 0.25146 1.6684 6.0390 1.1e-013 1.6720 0.016 AGH 0.57545 1.2565 3.9045 9.2e-010 1.2776 6.5e-006 ABG 0.57545 1.2565 3.9045 9.2e-010 1.2776 6.5e-006 ABH 0.57545 1.2565 3.9045 9.2e-010 1.2776 6.5e-006 BGH 0.57545 1.2565 3.9045 9.2e-010 1.2776 6.5e-006 BF 0.35707 1.5462 3.7769 1.3e-012 1.5534 0.00051 AD 0.32514 1.5842 3.4089 8.8e-013 1.5908 0.00035 AG 0.32043 1.5897 3.3576 8.3e-013 1.5963 0.00034 All models sorted together by BayesPostProb (best 15 out of 92): Model AdjRsq Rmse Fstat Likelihood Rmsec BPostProb* ----------------------------------------------------------------------- ADF 0.90790 0.5852 22.1230 0.00019 0.6389 0.21 BDF 0.90790 0.5852 22.1230 0.00019 0.6389 0.21 ABD 0.90790 0.5852 22.1230 0.00019 0.6389 0.21 ABF 0.90790 0.5852 22.1230 0.00019 0.6389 0.21 A 0.38039 1.5179 10.2089 5.1e-013 1.5234 0.065 AB 0.66061 1.1234 10.7323 2.1e-010 1.1382 0.054 B 0.25146 1.6684 6.0390 1.1e-013 1.6720 0.016 F 0.12526 1.8036 3.1480 3.2e-014 1.8056 0.005 AF 0.50710 1.3539 6.1441 1.1e-011 1.3641 0.0035 D -0.03104 1.9581 0.5484 8.6e-015 1.9585 0.0015 G -0.04819 1.9743 0.3104 7.5e-015 1.9745 0.0013 H -0.06331 1.9885 0.1069 6.7e-015 1.9886 0.0012 C -0.06836 1.9932 0.0403 6.5e-015 1.9932 0.0011 E -0.07100 1.9957 0.0056 6.3e-015 1.9957 0.0011 BF 0.35707 1.5462 3.7769 1.3e-012 1.5534 0.00051 Posterior weights that factors are active: Weighting models by Fstat: A: 148.413 0.64150 ******************* B: 128.462 0.55526 ***************** C: 31.2862 0.13523 **** D: 87.0813 0.37640 *********** E: 31.3069 0.13532 **** F: 105.66 0.45670 ************** G: 35.3893 0.15297 ***** H: 33.5595 0.14506 **** Weighting models by Bayesian post.prob. (pi=0.25, gam=2.5): A: 0.759569 0.75957 *********************** B: 0.706903 0.70690 ********************* C: 0.00146293 0.00146 D: 0.638422 0.63842 ******************* E: 0.00143614 0.00144 F: 0.645652 0.64565 ******************* G: 0.00178393 0.00178 H: 0.00155128 0.00155