PROGRAM  ISDTPCM CLUSPAC
FOR CLUSTERING MULTIVARIATE DATA
USING DISTANCE IN THE METRIC OF THE COVARIANCE MATRIX
 
 
DEVELOPED AND PROGRAMMED BY DR. STANLEY L. SCLOVE
 
VERSION 5.4   19-SEP-91
 
 
PREVIOUS UPDATE:  VERSION 5.3   15-MAR-88
COPYRIGHT (C) 1991 STANLEY L. SCLOVE.  ALL RIGHTS RESERVED.
 
....................................................................
 
CMS DSN = IQ DAT; X's:  Language IQ; Nonlanguage IQ
 
N =  23
NUMBER OF VARIABLES =  2
MINIMUM FOR EACH VARIABLE:  80.0  80.0
MAXIMUM FOR EACH VARIABLE:  119.0 124.0
 
 
K =  3 CLUSTERS
 
INITIAL MEANS
 
         90.0  90.0
        110.0 110.0
        100.0 120.0
 
CLUSTERING:
 
CASES AND LABELS:--
 
   1  1    2  1    3  1    4  1    5  1    6  1    7  1    8  1    9  1   10  1   11  1   12  1   13  3   14  3   15  2
  16  1   17  3   18  2   19  2   20  2   21  2   22  2   23  2
 
COMMON COVARIANCE MATRIX (MLE):
 
     37.03615     23.81796
     23.81796     42.21500
 
DET =     996.18582  IDET =   0     ACTUAL DET. = DET*10**IDET
 
 
INVERSE COVARIANCE MATRIX:
 
      0.04238     -0.02391
     -0.02391      0.03718
 
     MINUS 2 LOG LIKELIHOOD =     289.33276
 
 
ITERATION  1
 
MEAN VECTOR FOR CLUSTER  1:       90.23077     92.53846
MEAN VECTOR FOR CLUSTER  2:      109.14286    107.57143
MEAN VECTOR FOR CLUSTER  3:      102.33333    117.00000
 
 
CLUSTERING:
 
CASES AND LABELS:--
 
   1  1    2  1    3  1    4  1    5  1    6  1    7  1    8  1    9  1   10  1   11  1   12  1   13  3   14  3   15  2
  16  2   17  3   18  2   19  2   20  2   21  3   22  2   23  2
 
 
COMMON COVARIANCE MATRIX (MLE):
 
     34.52640     26.27640
     26.27640     41.68944
 
DET =     748.93715  IDET =   0     ACTUAL DET. = DET*10**IDET
 
 
INVERSE COVARIANCE MATRIX:
 
      0.05566     -0.03508
     -0.03508      0.04610
 
     MINUS 2 LOG LIKELIHOOD =     282.77124
 
 
 
ITERATION  2
 
MEAN VECTOR FOR CLUSTER  1:       89.25000     92.50000
MEAN VECTOR FOR CLUSTER  2:      107.85714    103.85714
MEAN VECTOR FOR CLUSTER  3:      104.50000    117.50000
 
 
CLUSTERING:
 
CASES AND LABELS:--
 
   1  1    2  1    3  1    4  1    5  1    6  1    7  1    8  1    9  1   10  1   11  1   12  1   13  3   14  3   15  2
  16  2   17  3   18  2   19  2   20  2   21  3   22  2   23  2
 
COMMON COVARIANCE MATRIX (MLE):
 
     34.52640     26.27640
     26.27640     41.68944
 
DET =     748.93715  IDET =   0     ACTUAL DET. = DET*10**IDET
 
INVERSE COVARIANCE MATRIX:
 
 
      0.05566     -0.03508
     -0.03508      0.04610
 
     MINUS 2 LOG LIKELIHOOD =     282.77124
 
 
ITERATION  3
 
MEAN VECTOR FOR CLUSTER  1:       89.25000     92.50000
MEAN VECTOR FOR CLUSTER  2:      107.85714    103.85714
MEAN VECTOR FOR CLUSTER  3:      104.50000    117.50000
 
CONVERGENCE:  NO CASE CHANGED CLUSTERS AFTER ITERATION  3.
RESULTS ARE PRINTED BELOW.
 
 
NUMBERS:           12            7            4
 
 
COMMON COVARIANCE MATRIX (UNBIASED ESTIMATE):
 
     39.70535     30.21785
     30.21785     47.94286
 
 
CASE, LABEL / DATA
 
   1  1  80.0  93.0
   2  1  82.0  91.0
   3  1  84.0  80.0
   4  1  86.0  94.0
   5  1  86.0  92.0
   6  1  89.0  94.0
   7  1  90.0  87.0
   8  1  94.0  87.0
   9  1  94.0  93.0
  10  1  95.0  97.0
  11  1  95.0 100.0
  12  1  96.0 102.0
  13  3  99.0 117.0
  14  3  99.0 110.0
  15  2 102.0 104.0
  16  2 102.0  93.0
  17  3 109.0 124.0
  18  2 104.0 103.0
  19  2 105.0  96.0
  20  2 105.0 100.0
  21  3 111.0 119.0
  22  2 118.0 115.0
  23  2 119.0 116.0
 
 
NUMBER OF PARAMETERS =    9
AIC =       300.77124
SCHWARZ CRITERION =       310.99048
 
PROGRAM ENDED NORMALLY.