1                                        
 
 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
1
 
 K =  2 CLUSTERS
 
 
 INITIAL MEANS
 
 
         100.0 100.0
 
         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  2   14  1   15  1
   16  1   17  2   18  1   19  1   20  1   21  2   22  2   23  2
 
 
 
 COMMON COVARIANCE MATRIX (MLE):
 
 
      59.56135     24.22319
      24.22319     39.77391
 
 DET =    1782.22520  IDET =   0     ACTUAL DET. = DET*10**IDET
 
 
 
 
 
 INVERSE COVARIANCE MATRIX:
 
 
       0.02232     -0.01359
      -0.01359      0.03342
 
      MINUS 2 LOG LIKELIHOOD =     302.71143
 
 
 
 ITERATION  1
 
 
 MEAN VECTOR FOR CLUSTER  1:       93.77778     95.33333
 MEAN VECTOR FOR CLUSTER  2:      111.20000    118.20000
 
 
 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  1
   16  1   17  2   18  1   19  1   20  1   21  2   22  2   23  2
 
 
 
 COMMON COVARIANCE MATRIX (MLE):
 
 
      63.69864     24.32182
      24.32182     32.30733
 
 DET =    1466.38182  IDET =   0     ACTUAL DET. = DET*10**IDET
 
 
 
 
 
 INVERSE COVARIANCE MATRIX:
 
 
       0.02203     -0.01659
      -0.01659      0.04344
 
      MINUS 2 LOG LIKELIHOOD =     298.22485
 
 
 
 ITERATION  2
 
 
 MEAN VECTOR FOR CLUSTER  1:       93.47059     94.47059
 MEAN VECTOR FOR CLUSTER  2:      109.16667    116.83333
 
 
 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  1
   16  1   17  2   18  1   19  1   20  1   21  2   22  2   23  2
 
 
 
 COMMON COVARIANCE MATRIX (MLE):
 
 
      63.69864     24.32182
      24.32182     32.30733
 
 DET =    1466.38182  IDET =   0     ACTUAL DET. = DET*10**IDET
 
 
 
 
 
 INVERSE COVARIANCE MATRIX:
 
 
       0.02203     -0.01659
      -0.01659      0.04344
 
      MINUS 2 LOG LIKELIHOOD =     298.22485
 
 
 
 ITERATION  3
 
 
 MEAN VECTOR FOR CLUSTER  1:       93.47059     94.47059
 MEAN VECTOR FOR CLUSTER  2:      109.16667    116.83333
 
 CONVERGENCE:  NO CASE CHANGED CLUSTERS AFTER ITERATION  3.  RESULTS ARE PRINTED BELOW.
 
 
 
 NUMBERS:           17            6
 
 
 
 COMMON COVARIANCE MATRIX (UNBIASED ESTIMATE):
 
 
      69.76517     26.63818
      26.63818     35.38422
 
 
 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  1
         102.0 104.0
   16  1
         102.0  93.0
   17  2
         109.0 124.0
   18  1
         104.0 103.0
   19  1
         105.0  96.0
   20  1
         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 =       312.22485
 
 SCHWARZ CRITERION =       320.17310
 
 PROGRAM ENDED NORMALLY.