@heading       number right $$
 
 
iq.isdtpcm     (SCLOVE)                                          p.$$
---------------------------------------------------------------------
 
@end
 
 
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 =  2 CLUSTERS
 
INITIAL MEANS
 
         90.0  90.0
 
        110.0 110.0
 
 
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  2   14  2   15  2
  16  1   17  2   18  2   19  2   20  2   21  2   22  2   23  2
 
 
 
@unit
COMMON COVARIANCE MATRIX (MLE):
 
     42.03077     13.81672
     13.81672     50.33177
 
DET =    1924.58130  IDET =   0     ACTUAL DET. = DET*10**IDET
 
 
@end
@UNIT
INVERSE COVARIANCE MATRIX:
 
      0.02615     -0.00718
     -0.00718      0.02184
 
     MINUS 2 LOG LIKELIHOOD =     304.47876
 
 
@end
ITERATION  1
 
MEAN VECTOR FOR CLUSTER  1:       90.23077     92.53846
MEAN VECTOR FOR CLUSTER  2:      106.40000    110.40000
 
 
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  2   14  2   15  2 16  1   17  2
  18  2   19  2   20  2   21  2   22  2   23  2
 
 
 
COMMON COVARIANCE MATRIX (MLE):
 
     42.03077     13.81672
     13.81672     50.33177
 
DET =    1924.58130  IDET =   0     ACTUAL DET. = DET*10**IDET
 
 
 
INVERSE COVARIANCE MATRIX:
 
      0.02615     -0.00718
     -0.00718      0.02184
 
     MINUS 2 LOG LIKELIHOOD =     304.47876
 
 
ITERATION  2
 
 
MEAN VECTOR FOR CLUSTER  1:       90.23077     92.53846
MEAN VECTOR FOR CLUSTER  2:      106.40000    110.40000
 
CONVERGENCE:  NO CASE CHANGED CLUSTERS AFTER ITERATION  2.  RESULTS
ARE PRINTED BELOW.
 
 
NUMBERS:           13           10
 
 
COMMON COVARIANCE MATRIX (UNBIASED ESTIMATE):
 
     46.03369     15.13260
     15.13260     55.12527
 
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  2 99.0 117.0
  14  2 99.0 110.0
  15  2 102.0 104.0
  16  1 102.0  93.0
  17  2 102.0 124.0
  18  2 104.0 103.0
  19  2 105.0  96.0
  20  2 105.0 100.0
  21  2 111.0 119.0
  22  2 118.0 115.0
  23  2 119.0 116.0
 
 
NUMBER OF PARAMETERS =    7
 
AIC = 318.47876
SCHWARZ CRITERION = 326.42700
 
 
 
PROGRAM ENDED NORMALLY.