Output from linpro2.sas	Source 1 Graph

                     LINEARLY OPTIMAL PROFILES ALGORITHM                     1
                          Data: Crime in U.S. cities

                       Analyzing the correlation matrix


   C          MURDER     RAPE  ROBBERY  ASSAULT BURGLARY  LARCENY AUTO_THF

   MURDER      1.000    0.435    0.437    0.556    0.232   -0.068    0.050
   RAPE        0.435    1.000    0.315    0.772    0.497    0.457    0.378
   ROBBERY     0.437    0.315    1.000    0.606    0.340    0.320    0.507
   ASSAULT     0.556    0.772    0.606    1.000    0.420    0.342    0.378
   BURGLARY    0.232    0.497    0.340    0.420    1.000    0.759    0.269
   LARCENY    -0.068    0.457    0.320    0.342    0.759    1.000    0.312
   AUTO_THF    0.050    0.378    0.507    0.378    0.269    0.312    1.000

                    Eigenvalues and Variance Accounted for

                      VAL  EIGVALUE   %_TRACE     CUM_%

                          3.4514042 49.305775 49.305775
                           1.332897 19.041385  68.34716
                           0.940294 13.432772 81.779932
                          0.6269497 8.9564241 90.736356
                          0.3659326  5.227608 95.963964
                           0.169939    2.4277 98.391664
                          0.1125835 1.6083361       100



     TABLE         MEAN   STD_DEV     EIGV1     EIGV2     SCALE  POSITION

     MURDER        9.75 4.7536828 0.2838442 0.6071861       1.3 2.1391529
     RAPE      28.11875 11.675734 0.4365507 0.0606574       5.1  0.138947
     ROBBERY      243.5 152.22886  0.384326 0.1927698      58.5 0.5015789
     ASSAULT     196.25 81.767582 0.4601646 0.2671038      37.6 0.5804528
     BURGLARY 1375.6875 295.36349 0.3894826 -0.395026       115 -1.014232
     LARCENY   1003.625 253.21924  0.348187 -0.591258      88.2 -1.698105
     AUTO_THF   689.125 146.06029 0.3105916 -0.116231      45.4 -0.374226

                 TABLE, with variables reordered by position

     TABLE         MEAN   STD_DEV     EIGV1     EIGV2     SCALE  POSITION

     LARCENY   1003.625 253.21924  0.348187 -0.591258      88.2 -1.698105
     BURGLARY 1375.6875 295.36349 0.3894826 -0.395026       115 -1.014232
     AUTO_THF   689.125 146.06029 0.3105916 -0.116231      45.4 -0.374226
     RAPE      28.11875 11.675734 0.4365507 0.0606574       5.1  0.138947
     ROBBERY      243.5 152.22886  0.384326 0.1927698      58.5 0.5015789
     ASSAULT     196.25 81.767582 0.4601646 0.2671038      37.6 0.5804528
     MURDER        9.75 4.7536828 0.2838442 0.6071861       1.3 2.1391529

                                  Case lines

                     F                 INTERCPT     SLOPE

                     LINEARLY OPTIMAL PROFILES ALGORITHM                     2
                          Data: Crime in U.S. cities

                     Atlanta          -2.988015 4.2621165
                     Boston           -5.375175 -0.911191
                     Chicago          -2.492739 6.1433266
                     Dallas           3.0576399 4.2283063
                     Denver           2.6163506  -4.61279
                     Detroit          5.1869873 0.3809394
                     Hartford          -9.30564 -1.059204
                     Honolulu          -5.68872 -5.614655
                     Houston          1.1763028 4.2063252
                     Kansas City       2.679952 0.6264686
                     Los Angeles      8.7139464 -3.288146
                     New Orleans      1.9566345 1.7333419
                     New York         5.5058415 -2.877271
                     Portland          -2.40402 -4.729004
                     Tucson            -6.01614 -0.254678
                     Washington        3.376795 1.7661149

                                Fitted values

   FIT               LARCENY BURGLARY AUTO_THF     RAPE  ROBBERY  ASSAULT
   :                  MURDER

   Atlanta           -10.226   -7.311   -4.583   -2.396   -0.850   -0.514
   :                   6.129

   Boston             -3.828   -4.451   -5.034   -5.502   -5.832   -5.904
   :                  -7.324

   Chicago           -12.925   -8.723   -4.792   -1.639    0.589    1.073
   :                  10.649

   Dallas             -4.122   -1.231    1.475    3.645    5.178    5.512
   :                  12.103

   Denver             10.449    7.295    4.343    1.975    0.303   -0.061
   :                  -7.251

   Detroit             4.540    4.801    5.044    5.240    5.378    5.408
   :                   6.002

   Hartford           -7.507   -8.231   -8.909   -9.453   -9.837   -9.920
   :                 -11.571

   Honolulu            3.846    0.006   -3.588   -6.469   -8.505   -8.948
   :                 -17.699

   Houston            -5.966   -3.090   -0.398    1.761    3.286    3.618
   :                  10.174

   Kansas City         1.616    2.045    2.446    2.767    2.994    3.044
   :                   4.020

                     LINEARLY OPTIMAL PROFILES ALGORITHM                     3
                          Data: Crime in U.S. cities

   Los Angeles        14.298   12.049    9.944    8.257    7.065    6.805
   :                   1.680

   New Orleans        -0.987    0.199    1.308    2.197    2.826    2.963
   :                   5.665

   New York           10.392    8.424    6.583    5.106    4.063    3.836
   :                  -0.649

   Portland            5.626    2.392   -0.634   -3.061   -4.776   -5.149
   :                 -12.520

   Tucson             -5.584   -5.758   -5.921   -6.052   -6.144   -6.164
   :                  -6.561

   Washington          0.378    1.586    2.716    3.622    4.263    4.402
   :                   7.155


                                  Residuals

   RESID             LARCENY BURGLARY AUTO_THF     RAPE  ROBBERY  ASSAULT
   :                  MURDER

   Atlanta             9.107    5.019    0.282    1.745   -1.500   -0.795
   :                  -1.127

   Boston              0.033    1.029   10.873    2.594    3.755    3.080
   :                   3.211

   Chicago             8.449    3.789    3.819    0.968    1.061    0.143
   :                  -9.278

   Dallas              2.958    3.772   -3.396   -2.452   -6.195   -2.941
   :                  -5.914

   Denver             -6.317   -5.919   -2.339    0.650   -1.508   -0.078
   :                   5.139

   Detroit            -2.506   -3.146   -2.865   -3.753   -1.387   -4.777
   :                  -3.593

   Hartford            4.335    5.113    4.035    5.663    6.837    7.442
   :                   6.198

   Honolulu           -2.730    0.701    2.439    3.444    5.061    4.476
   :                  13.141

   Houston             3.510    4.249    0.571   -2.059   -2.508   -3.890
   :                  -4.949

   Kansas City        -2.168   -1.016   -0.773    0.192   -2.798   -2.253

                     LINEARLY OPTIMAL PROFILES ALGORITHM                     4
                          Data: Crime in U.S. cities

   :                  -3.242

   Los Angeles        -9.961   -7.474   -6.134   -3.611   -6.338   -2.586
   :                  -1.717

   New Orleans         1.354   -2.978    0.607    0.075   -2.441   -0.657
   :                  -5.257

   New York           -5.987   -5.831   -3.080   -6.817    0.698   -1.955
   :                   0.390

   Portland           -2.480   -1.051   -3.799    2.057    3.297    3.760
   :                   9.000

   Tucson              2.786    4.283    1.377    5.028    3.435    4.882
   :                   3.115

   Washington         -0.385   -0.540   -1.616   -3.724    0.532   -3.850
   :                  -5.117



                         SSE       SSF       SST       VAF
                   2080.1831 4445.5692 869.73933 0.6812347


                         SSE       SSF       SST       VAF
                   3170887.6 4445.5692 3243386.7    0.0014

                     LINEARLY OPTIMAL PROFILES ALGORITHM                     5
                          Data: Crime in U.S. cities
              R E S I D U A L S, bordered by fitted coefficients

   RL              LARCENY    BURGLARY    AUTO_THF        RAPE     ROBBERY

   Atlanta            9.11        5.02        0.28        1.74       -1.50
   Boston             0.03        1.03       10.87        2.59        3.76
   Chicago            8.45        3.79        3.82        0.97        1.06
   Dallas             2.96        3.77       -3.40       -2.45       -6.20
   Denver            -6.32       -5.92       -2.34        0.65       -1.51
   Detroit           -2.51       -3.15       -2.86       -3.75       -1.39
   Hartford           4.34        5.11        4.03        5.66        6.84
   Honolulu          -2.73        0.70        2.44        3.44        5.06
   Houston            3.51        4.25        0.57       -2.06       -2.51
   Kansas City       -2.17       -1.02       -0.77        0.19       -2.80
   Los Angeles       -9.96       -7.47       -6.13       -3.61       -6.34
   New Orleans        1.35       -2.98        0.61        0.07       -2.44
   New York          -5.99       -5.83       -3.08       -6.82        0.70
   Portland          -2.48       -1.05       -3.80        2.06        3.30
   Tucson             2.79        4.28        1.38        5.03        3.43
   Washington        -0.38       -0.54       -1.62       -3.72        0.53
   VARIABLE          -1.70       -1.01       -0.37        0.14        0.50
   SCALE             88.20      115.00       45.40        5.10       58.50

   RL              ASSAULT      MURDER    INTERCPT       SLOPE

   Atlanta           -0.79       -1.13       -2.99        4.26
   Boston             3.08        3.21       -5.38       -0.91
   Chicago            0.14       -9.28       -2.49        6.14
   Dallas            -2.94       -5.91        3.06        4.23
   Denver            -0.08        5.14        2.62       -4.61
   Detroit           -4.78       -3.59        5.19        0.38
   Hartford           7.44        6.20       -9.31       -1.06
   Honolulu           4.48       13.14       -5.69       -5.61
   Houston           -3.89       -4.95        1.18        4.21
   Kansas City       -2.25       -3.24        2.68        0.63
   Los Angeles       -2.59       -1.72        8.71       -3.29
   New Orleans       -0.66       -5.26        1.96        1.73
   New York          -1.96        0.39        5.51       -2.88
   Portland           3.76        9.00       -2.40       -4.73
   Tucson             4.88        3.11       -6.02       -0.25
   Washington        -3.85       -5.12        3.38        1.77
   VARIABLE           0.58        2.14        3.45        0.00
   SCALE             37.60        1.30        0.00       49.31

                                                                             6

Graphic output from linpro2.sas

PLOT OF FIT * POSITION = CITY [ LINPRO 09/28/99 ]