1**************************************** PROGRAM CLASSPDT FOR CLASSIFYING MULTIVARIATE DATA USING DISTANCE IN THE METRICS OF THE COVARIANCE MATRICES ADJUSTED BY THE DETERMINANTS DEVELOPED AND PROGRAMMED BY DR. STANLEY L. SCLOVE VERSION 1.0 13-NOV-93 CLUSPAC PROGRAMS COPYRIGHT 1991, 1992, 1993 STANLEY LOUIS SCLOVE. CMS DSN = RLESTATE DATAMLLR; Xs: STYLE;SFLA;GRADE;ASSESSED;MARKET N = 60 NUMBER OF VARIABLES = 5 MINIMUM FOR EACH VARIABLE: 0.99 5.21 0.74 6.90 29.1 MAXIMUM FOR EACH VARIABLE: 2.00 18.04 1.00 48.30 72.6 1 K = 3 POPULATIONS INITIAL MEANS 1.00 7.00 0.50 15.00 30.0 1.00 9.23 0.75 6.90 45.0 1.20 11.00 1.00 45.00 70.0 .49.02.49 COVARIANCE MATRICES: 0.25 0.10 0.10 0.10 0.10 0.10 1.24 0.10 0.10 0.10 0.10 0.10 0.25 0.10 0.10 0.10 0.10 0.10 9.00 0.20 0.10 0.10 0.10 0.10 2.10 0.25 0.10 0.10 0.10 0.10 0.10 1.24 0.10 0.10 0.10 0.10 0.10 0.25 0.10 0.10 0.10 0.10 0.10 9.00 0.20 0.10 0.10 0.10 0.10 2.10 0.25 0.10 0.10 0.10 0.10 0.10 1.24 0.10 0.10 0.10 0.10 0.10 0.25 0.10 0.10 0.10 0.10 0.10 9.00 0.20 0.10 0.10 0.10 0.10 2.10 4.88 -0.24 -1.79 -0.03 -0.13 -0.24 0.85 -0.24 0.00 -0.02 -1.79 -0.24 4.88 -0.03 -0.13 -0.03 0.00 -0.03 0.11 -0.01 -0.13 -0.02 -0.13 0.00 0.49 4.88 -0.24 -1.79 -0.03 -0.13 -0.24 0.85 -0.24 0.00 -0.02 -1.79 -0.24 4.88 -0.03 -0.13 -0.03 0.00 -0.03 0.11 -0.01 -0.13 -0.02 -0.13 0.00 0.49 4.88 -0.24 -1.79 -0.03 -0.13 -0.24 0.85 -0.24 0.00 -0.02 -1.79 -0.24 4.88 -0.03 -0.13 -0.03 0.00 -0.03 0.11 -0.01 -0.13 -0.02 -0.13 0.00 0.49 CLUSTERING: CASES AND LABELS:-- 1 3 2 2 3 3 4 2 5 3 6 2 7 3 8 3 9 3 10 3 11 3 12 3 13 2 14 3 15 3 16 1 17 1 18 3 19 3 20 3 21 3 22 3 23 3 24 3 25 1 26 3 27 3 28 2 29 2 30 2 31 3 32 3 33 2 34 3 35 3 36 3 37 2 38 2 39 3 40 2 41 2 42 3 43 3 44 2 45 3 46 3 47 3 48 2 49 2 50 3 51 3 52 3 53 3 54 3 55 2 56 3 57 2 58 3 59 2 60 3 NUMBERS: 3 18 39 .05.30.65 COMMON COVARIANCE MATRIX (MLE): 0.07446 0.37791 0.00247 0.04415 0.56639 0.37791 3.69765 0.02086 1.14410 5.24169 0.00247 0.02086 0.00252 0.04172 0.10846 0.04415 1.14410 0.04172 43.65435 12.28340 0.56639 5.24169 0.10846 12.28340 23.49282 DET = 0.15324 IDET = 0 ACTUAL DET. = DET*10**IDET INVERSE COVARIANCE MATRIX: 28.15006 -2.75831 -1.96609 0.07145 -0.09152 -2.75831 0.67814 0.99981 0.01081 -0.09508 -1.96609 0.99981 498.86943 0.23034 -2.59923 0.07145 0.01081 0.23034 0.02790 -0.01979 -0.09152 -0.09508 -2.59923 -0.01979 0.08833 MINUS 2 LOG LIKELIHOOD FOR MODEL WITH COMMON COVARIANCE MATRIX= 738.81909 NUMBER OF PARAMETERS = 30 AIC FOR MODEL WITH COMMON COVARIANCE MATRIX = 798.81909 SCHWARZ CRITERION FOR MODEL WITH COMMON COVARIANCE MATRIX = 861.64941 MINUS 2 LOG LIKELIHOOD FOR MODEL WITH DIFFERENT COVARIANCE MATRICES = 851.36304 NUMBER OF PARAMETERS = 60 AIC FOR MODEL WITH DIFFERENT COVARIANCE MATRICES = 971.36304 SCHWARZ CRITERION FOR MODEL WITH DIFFERENT COVARIANCE MATRICES = 1097.02368 MEAN VECTOR FOR CLUSTER 1: 1.00000 5.53000 0.80000 36.80000 35.40000 MEAN VECTOR FOR CLUSTER 2: 1.06222 7.89611 0.81667 26.81833 49.40000 MEAN VECTOR FOR CLUSTER 3: 1.30128 10.41846 0.91026 39.16154 61.70769