28
**** problem e1 ****
10
-
 Example Frome '84 pp. 8-10 (Table 2, In-Vitro Dose Response, 192 Ir radiation)
  20   2   1   2   2   6   6
 (1X,F5.0,F4.0,F4.1,F6.2)
     0  50 0.5  0.25
     1  50 0.5  0.25
     0  50 0.5  0.25
     2  50 0.5  0.25
     1  50 0.5  0.25
     3  50 0.5  0.25
     2  50 0.5  0.25
     5  50 1.0  1.0
     6  50 1.0  1.0
     5  50 1.0  1.0
     4  50 1.0  1.0
     8  50 1.0  1.0
    16  50 2.0  4.0
    17  50 2.0  4.0
    18  50 2.0  4.0
    49  50 4.0 16.0
    59  50 4.0 16.0
    54  50 4.0 16.0
    56  50 4.0 16.0
    63  50 4.0 16.0
7


28
**** problem e2.2 ****
10
-
 Data for model (2.2) in Frome '84.
  27   3   1   3   2   6   6
 (1X,F4.0,F6.2,F5.1,F6.2,F9.4)
  25.  4.78  1.0  1.00  -1.000
 102. 19.07  1.0  1.00  -0.6021
 149. 22.58  1.0  1.00  -0.3010
 160. 23.29  1.0  1.00   0.0000
  75. 12.38  1.0  1.00   0.1761
 100. 14.91  1.0  1.00   0.3010
  99. 15.18  1.0  1.00   0.3979
  50.  7.64  1.0  1.00   0.4771
 100. 13.67  1.0  1.00   0.6021
  52.  3.28  2.5  6.25  -6.250
  51.  1.85  2.5  6.25  -3.763
 100.  3.42  2.5  6.25  -1.881
 100.  3.10  2.5  6.25   0.000
 107.  2.78  2.5  6.25   1.101
 107.  2.59  2.5  6.25   1.881
 102.  2.49  2.5  6.25   2.487
 110.  2.98  2.5  6.25   2.982
 107.  2.43  2.5  6.25   3.763
 100.  2.10  5.0 25.00 -25.00
 113.  1.38  5.0 25.00 -15.051
 144.  1.60  5.0 25.00  -7.526
 106.  1.20  5.0 25.00   0.000
 111.  0.90  5.0 25.00   4.402
 132.  1.00  5.0 25.00   7.526
 419.  3.13  5.0 25.00   9.949
 225.  1.82  5.0 25.00  11.928
 206.  1.44  5.0 25.00  15.051
7


28
**** problem e2.6 ****
10
-
 Data for model (2.6) in Frome '84.
  27   3   5   2   2   6   6
       8.0       1.0      3.1
 (1X,F4.0,F6.2,F4.1,F7.3)
  25.  4.78 1.0 10.000
 102. 19.07 1.0  4.000
 149. 22.58 1.0  2.000
 160. 23.29 1.0  1.000
  75. 12.38 1.0  0.667
 100. 14.91 1.0  0.500
  99. 15.18 1.0  0.400
  50.  7.64 1.0  0.333
 100. 13.67 1.0  0.250
  52.  3.28 2.5 25.000
  51.  1.85 2.5 10.000
 100.  3.42 2.5  5.000
 100.  3.10 2.5  2.500
 107.  2.78 2.5  1.667
 107.  2.59 2.5  1.125
 102.  2.49 2.5  1.000
 110.  2.98 2.5  0.833
 107.  2.43 2.5  0.625
 100.  2.10 5.0 50.000
 113.  1.38 5.0 20.000
 144.  1.60 5.0 10.000
 106.  1.20 5.0  5.000
 111.  0.90 5.0  3.333
 132.  1.00 5.0  2.250
 419.  3.13 5.0  2.000
 225.  1.82 5.0  1.667
 206.  1.44 5.0  1.125
7


28
**** problem e2.8 ****
10
-
 Data for model (2.8) in Frome '84.
  30   4   6   2   2   6   6
       3.0       2.0     1.0      3.0
 (1X,F4.0,F8.0,F9.4,F9.4)
   0.  35164.  -0.7538 -100.000
   0.   3657.  -0.7538  -0.6931
   0.   8063.  -0.7538   1.6094
   2.  59965.  -0.7538   2.7081
   4.  40643.  -0.7538   3.4012
   0.   3992.  -0.7538   3.8067
   0.  15134.  -0.3483 -100.000
   0.   1283.  -0.3483  -0.6931
   0.   3129.  -0.3483   1.6094
   2.  16392.  -0.3483   2.7081
  10.  12839.  -0.3483   3.4012
   2.   1928.  -0.3483   3.8067
  25. 213858. -0.06062 -100.000
   6.  14624. -0.06062  -0.6931
  31.  45217. -0.06062   1.6094
 183. 151664. -0.06062   2.7081
 245. 103020. -0.06062   3.4012
  63.  19649. -0.06062   3.8067
  49. 171211.   0.1625 -100.000
  10.  10053.   0.1625  -0.6931
  44.  37130.   0.1625   1.6094
 239. 101731.   0.1625   2.7081
 194.  50045.   0.1625   3.4012
  50.   8937.   0.1625   3.8067
   4.   8489.   0.3448 -100.000
   1.    512.   0.3448  -0.6931
   5.   1923.   0.3448   1.6094
  15.   3867.   0.3448   2.7081
   7.   1273.   0.3448   3.4012
   3.    232.   0.3448   3.8067
7


28
**** problem e3.1 ****
10
-
 Data for model (3.1) in Frome '84.
   5   2   1   2   6   6   6
 (1X,F4.0,2F5.0,F6.0)
  15. 600.  1.0   0.0
  96. 500.  1.0  30.0
 187. 600.  1.0  60.0
 100. 300.  1.0  75.0
 145. 300.  1.0  90.0
7


28
**** problem e3.3 ****
10
-
 Data for model (3.3) in Frome '84.
   5   2   7   2   6   6   6
.0317714  .00467588
 (1X,F4.0,2F5.0,F6.0)
  15. 600.  1.0   0.0
  96. 500.  1.0  30.0
 187. 600.  1.0  60.0
 100. 300.  1.0  75.0
 145. 300.  1.0  90.0
7


28
**** problem e3.5 ****
10
-
 Model (3.5), p. 25 of Frome '84
  72   9   1   9   8
 (1x,f5.0,f4.0,f11.0,9f3.0)
     0 199  -0.287682 1. 0. 0. 0. 0. 0. 0. 0.
     0 164   0.000000 1. 0. 0. 0. 0. 0. 0. 0.
     1 133   0.154151 1. 0. 0. 0. 0. 0. 0. 0.
     0 115   0.223144 1. 0. 0. 0. 0. 0. 0. 0.
     1 205   0.287682 1. 0. 0. 0. 0. 0. 0. 0.
     0 153   0.348307 1. 0. 0. 0. 0. 0. 0. 0.
     6 555   0.405465 1. 0. 0. 0. 0. 0. 0. 0.
    20 762   0.693147 1. 0. 0. 0. 0. 0. 0. 0.
    17 100   1.011601 1. 0. 0. 0. 0. 0. 0. 0.
     1 147  -0.287682 0. 1. 0. 0. 0. 0. 0. 0.
     1  51   0.000000 0. 1. 0. 0. 0. 0. 0. 0.
     1  42   0.154151 0. 1. 0. 0. 0. 0. 0. 0.
     1  75   0.223144 0. 1. 0. 0. 0. 0. 0. 0.
     2  66   0.287682 0. 1. 0. 0. 0. 0. 0. 0.
     4  69   0.348307 0. 1. 0. 0. 0. 0. 0. 0.
    342014   0.405465 0. 1. 0. 0. 0. 0. 0. 0.
   1642109   0.693147 0. 1. 0. 0. 0. 0. 0. 0.
   135 445   1.011601 0. 1. 0. 0. 0. 0. 0. 0.
     1  76  -0.287682 0. 0. 1. 0. 0. 0. 0. 0.
     2  27   0.000000 0. 0. 1. 0. 0. 0. 0. 0.
     0  25   0.154151 0. 0. 1. 0. 0. 0. 0. 0.
     1  35   0.223144 0. 0. 1. 0. 0. 0. 0. 0.
     2  61   0.287682 0. 0. 1. 0. 0. 0. 0. 0.
     5 443   0.348307 0. 0. 1. 0. 0. 0. 0. 0.
    201102   0.405465 0. 0. 1. 0. 0. 0. 0. 0.
   1281361   0.693147 0. 0. 1. 0. 0. 0. 0. 0.
    72 200   1.011601 0. 0. 1. 0. 0. 0. 0. 0.
     0  52  -0.287682 0. 0. 0. 1. 0. 0. 0. 0.
     1  14   0.000000 0. 0. 0. 1. 0. 0. 0. 0.
     2  14   0.154151 0. 0. 0. 1. 0. 0. 0. 0.
     0  20   0.223144 0. 0. 0. 1. 0. 0. 0. 0.
     3 304   0.287682 0. 0. 0. 1. 0. 0. 0. 0.
     6 302   0.348307 0. 0. 0. 1. 0. 0. 0. 0.
    15 550   0.405465 0. 0. 0. 1. 0. 0. 0. 0.
    98 888   0.693147 0. 0. 0. 1. 0. 0. 0. 0.
    42 103   1.011601 0. 0. 0. 1. 0. 0. 0. 0.
     0 345  -0.287682 0. 0. 0. 0. 1. 0. 0. 0.
     2 283   0.000000 0. 0. 0. 0. 1. 0. 0. 0.
     1 243   0.154151 0. 0. 0. 0. 1. 0. 0. 0.
     3 203   0.223144 0. 0. 0. 0. 1. 0. 0. 0.
     6 287   0.287682 0. 0. 0. 0. 1. 0. 0. 0.
     8 230   0.348307 0. 0. 0. 0. 1. 0. 0. 0.
    13 441   0.405465 0. 0. 0. 0. 1. 0. 0. 0.
   118 758   0.693147 0. 0. 0. 0. 1. 0. 0. 0.
    30  67   1.011601 0. 0. 0. 0. 1. 0. 0. 0.
     0 186  -0.287682 0. 0. 0. 0. 0. 1. 0. 0.
     0 153   0.000000 0. 0. 0. 0. 0. 1. 0. 0.
     0 124   0.154151 0. 0. 0. 0. 0. 1. 0. 0.
     1 109   0.223144 0. 0. 0. 0. 0. 1. 0. 0.
     7 193   0.287682 0. 0. 0. 0. 0. 1. 0. 0.
     9 166   0.348307 0. 0. 0. 0. 0. 1. 0. 0.
    17 382   0.405465 0. 0. 0. 0. 0. 1. 0. 0.
   118 587   0.693147 0. 0. 0. 0. 0. 1. 0. 0.
    37  75   1.011601 0. 0. 0. 0. 0. 1. 0. 0.
     1 168  -0.287682 0. 0. 0. 0. 0. 0. 1. 0.
     3 149   0.000000 0. 0. 0. 0. 0. 0. 1. 0.
     1 127   0.154151 0. 0. 0. 0. 0. 0. 1. 0.
     5  99   0.223144 0. 0. 0. 0. 0. 0. 1. 0.
     2 100   0.287682 0. 0. 0. 0. 0. 0. 1. 0.
     3  85   0.348307 0. 0. 0. 0. 0. 0. 1. 0.
    19 213   0.405465 0. 0. 0. 0. 0. 0. 1. 0.
    76 297   0.693147 0. 0. 0. 0. 0. 0. 1. 0.
    22  31   1.011601 0. 0. 0. 0. 0. 0. 1. 0.
     1 169  -0.287682 0. 0. 0. 0. 0. 0. 0. 1.
     2 152   0.000000 0. 0. 0. 0. 0. 0. 0. 1.
     1 127   0.154151 0. 0. 0. 0. 0. 0. 0. 1.
     1 100   0.223144 0. 0. 0. 0. 0. 0. 0. 1.
     7 110   0.287682 0. 0. 0. 0. 0. 0. 0. 1.
     1  82   0.348307 0. 0. 0. 0. 0. 0. 0. 1.
    24 211   0.405465 0. 0. 0. 0. 0. 0. 0. 1.
   126 314   0.693147 0. 0. 0. 0. 0. 0. 0. 1.
     9  11   1.011601 0. 0. 0. 0. 0. 0. 0. 1.
7


28
**** problem ex1 ****
10
-
  PRLRT1.DAT: RC3- BIOMETRICS ( 1965 ) P. 613
  11   2   1   2   2   6   6
 (1X,F5.0,F4.0,2F7.4)
    24   4 0.0500 0.0025
    90   5 0.1000 0.0100
   110   5 0.1500 0.0225
   160   5 0.2000 0.0400
   165   5 0.2500 0.0625
   220   5 0.3000 0.0900
   195   5 0.3500 0.1225
   245   5 0.4000 0.1600
   208   4 0.4500 0.2025
   295   5 0.5000 0.2500
   204   3 0.6000 0.3600
7


28
**** problem ex2 ****
10
-
 PRLLT3.DAT:  NELDER-WEDDERBURN (1972) P.378
  20   9   2   9   2   6   6
 (1X,F3.0,9F3.0,F4.0)
   7  1  1  0  0  0  0  0  0  0  -8
   3  1  1  0  0  0  0  1  0  0  -6
   4  1  1  0  0  0  0  0  1  0  -4
   7  1  1  0  0  0  0  0  0  1  -2
  13  1  1  1  0  0  0  0  0  0  -4
  11  1  1  1  0  0  0  1  0  0  -3
  15  1  1  1  0  0  0  0  1  0  -2
  10  1  1  1  0  0  0  0  0  1  -1
   7  1  1  0  1  0  0  0  0  0   0
  11  1  1  0  1  0  0  1  0  0   0
   9  1  1  0  1  0  0  0  1  0   0
  23  1  1  0  1  0  0  0  0  1   0
  10  1  1  0  0  1  0  0  0  0   4
  12  1  1  0  0  1  0  1  0  0   3
   9  1  1  0  0  1  0  0  1  0   2
  28  1  1  0  0  1  0  0  0  1   1
   3  1  1  0  0  0  1  0  0  0   8
   4  1  1  0  0  0  1  1  0  0   6
   5  1  1  0  0  0  1  0  1  0   4
  32  1  1  0  0  0  1  0  0  1   2
7


28
**** problem ex3 ****
10
-
 PRNLT1.DAT: TILL AND MCCUL. (1961) DATA-- TARGET MODEL
   7   3   3   2   3   6   6
       8.0       1.0      3.1
 (1X,F5.0,F5.0,F7.2,F5.2)
   60.   6.   1.25 0.00
   66.   7.   1.75 0.96
   46.   4.   3.00 1.92
   82.   9.   7.20 2.88
  105.  11.  24.00 4.32
  123.  15.  75.00 5.76
   12.   4. 120.00 6.72
7


28
**** problem ex8-10 ****
10
-
  Example Frome '84 pp. 8-10 (Table 2, In-Vitro Dose Response, 192 Ir radiation)
   4   2   1   2   2   6   6
 (1X,F5.0,F4.0,F4.1,F6.2)
     9 350 0.5  0.25
    28 250 1.0  1.0
    51 150 2.0  4.0
   281 250 4.0 16.0
7


28
**** problem mn202 ****
10
-
 Example on p. 202 of McCullagh and Nelder
  64   7  11   3  10   6   6
  1.,1.,40.,2.,22.,
  3.,32.
 (F5.2,F3.0,3F5.0)
 1.98 1.   0.   0.   0.
 2.38 1.   0.  22.   0.
 2.18 1.   0.  44.   0.
 2.22 1.   0.  88.   0.
 3.88 1. 100.   0.   0.
 4.35 1. 100.  22.   0.
 4.14 1. 100.  44.   0.
 4.26 1. 100.  88.   0.
 4.40 1. 200.   0.   0.
 5.01 1. 200.  22.   0.
 4.77 1. 200.  44.   0.
 5.17 1. 200.  88.   0.
 4.43 1. 400.   0.   0.
 4.95 1. 400.  22.   0.
 5.22 1. 400.  44.   0.
 5.66 1. 400.  88.   0.
 2.13 1.   0.   0.  42.
 2.24 1.   0.  22.  42.
 2.56 1.   0.  44.  42.
 2.47 1.   0.  88.  42.
 3.91 1. 100.   0.  42.
 4.59 1. 100.  22.  42.
 4.36 1. 100.  44.  42.
 4.72 1. 100.  88.  42.
 4.91 1. 200.   0.  42.
 5.64 1. 200.  22.  42.
 5.69 1. 200.  44.  42.
 5.45 1. 200.  88.  42.
 5.31 1. 400.   0.  42.
 6.27 1. 400.  22.  42.
 6.27 1. 400.  44.  42.
 6.24 1. 400.  88.  42.
 2.19 1.   0.   0.  84.
 2.10 1.   0.  22.  84.
 2.22 1.   0.  44.  84.
 2.94 1.   0.  88.  84.
 3.66 1. 100.   0.  84.
 4.47 1. 100.  22.  84.
 4.55 1. 100.  44.  84.
 4.83 1. 100.  88.  84.
 5.10 1. 200.   0.  84.
 5.68 1. 200.  22.  84.
 5.80 1. 200.  44.  84.
 5.85 1. 200.  88.  84.
 5.15 1. 400.   0.  84.
 6.49 1. 400.  22.  84.
 6.35 1. 400.  44.  84.
 7.11 1. 400.  88.  84.
 1.97 1.   0.   0. 168.
 2.60 1.   0.  22. 168.
 2.47 1.   0.  44. 168.
 2.48 1.   0.  88. 168.
 4.07 1. 100.   0. 168.
 4.55 1. 100.  22. 168.
 4.35 1. 100.  44. 168.
 4.85 1. 100.  88. 168.
 5.23 1. 200.   0. 168.
 5.60 1. 200.  22. 168.
 6.07 1. 200.  44. 168.
 6.43 1. 200.  88. 168.
 5.87 1. 400.   0. 168.
 6.54 1. 400.  22. 168.
 6.72 1. 400.  44. 168.
 7.32 1. 400.  88. 168.
7


28
**** problem mn202.1 ****
10
-
 Example on p. 202 of McCullagh and Nelder
  64   7  11   3  10   6   6
 1.,2.,3.,4.,5.
 6.,7.
 (F5.2,F3.0,3F5.0)
 1.98 1.   0.   0.   0.
 2.38 1.   0.  22.   0.
 2.18 1.   0.  44.   0.
 2.22 1.   0.  88.   0.
 3.88 1. 100.   0.   0.
 4.35 1. 100.  22.   0.
 4.14 1. 100.  44.   0.
 4.26 1. 100.  88.   0.
 4.40 1. 200.   0.   0.
 5.01 1. 200.  22.   0.
 4.77 1. 200.  44.   0.
 5.17 1. 200.  88.   0.
 4.43 1. 400.   0.   0.
 4.95 1. 400.  22.   0.
 5.22 1. 400.  44.   0.
 5.66 1. 400.  88.   0.
 2.13 1.   0.   0.  42.
 2.24 1.   0.  22.  42.
 2.56 1.   0.  44.  42.
 2.47 1.   0.  88.  42.
 3.91 1. 100.   0.  42.
 4.59 1. 100.  22.  42.
 4.36 1. 100.  44.  42.
 4.72 1. 100.  88.  42.
 4.91 1. 200.   0.  42.
 5.64 1. 200.  22.  42.
 5.69 1. 200.  44.  42.
 5.45 1. 200.  88.  42.
 5.31 1. 400.   0.  42.
 6.27 1. 400.  22.  42.
 6.27 1. 400.  44.  42.
 6.24 1. 400.  88.  42.
 2.19 1.   0.   0.  84.
 2.10 1.   0.  22.  84.
 2.22 1.   0.  44.  84.
 2.94 1.   0.  88.  84.
 3.66 1. 100.   0.  84.
 4.47 1. 100.  22.  84.
 4.55 1. 100.  44.  84.
 4.83 1. 100.  88.  84.
 5.10 1. 200.   0.  84.
 5.68 1. 200.  22.  84.
 5.80 1. 200.  44.  84.
 5.85 1. 200.  88.  84.
 5.15 1. 400.   0.  84.
 6.49 1. 400.  22.  84.
 6.35 1. 400.  44.  84.
 7.11 1. 400.  88.  84.
 1.97 1.   0.   0. 168.
 2.60 1.   0.  22. 168.
 2.47 1.   0.  44. 168.
 2.48 1.   0.  88. 168.
 4.07 1. 100.   0. 168.
 4.55 1. 100.  22. 168.
 4.35 1. 100.  44. 168.
 4.85 1. 100.  88. 168.
 5.23 1. 200.   0. 168.
 5.60 1. 200.  22. 168.
 6.07 1. 200.  44. 168.
 6.43 1. 200.  88. 168.
 5.87 1. 400.   0. 168.
 6.54 1. 400.  22. 168.
 6.72 1. 400.  44. 168.
 7.32 1. 400.  88. 168.
7


28
**** problem mn204 ****
10
-
 Example on p. 205 of McCullagh and Nelder
  15   4   9   2   7   6   6
  1., 1., 1., 1.
 (1X,F3.0,F4.0,F4.0,F6.2)
   7 100  4.  0.
  59 200  5.  0.
 115 300  8.  0.
 149 300 10.  0.
 178 300 15.  0.
 229 300 20.  0.
   5 100  2.  3.9
  43 100  5.  3.9
  76 100 10.  3.9
   4 100  2.  19.5
  57 100  5.  19.5
  83 100 10.  19.5
   6 100  2.  39.
  57 100  5.  39.
  84 100 10.  39.
7


28
**** problem mn205 ****
10
-
 Example on p. 204-5 of McCullagh and Nelder
  15   5  10   2   7   6   6
  1., 1., 1., 1., 1.
 (1X,F3.0,F4.0,F4.0,F6.2)
   7 100  4.  0.
  59 200  5.  0.
 115 300  8.  0.
 149 300 10.  0.
 178 300 15.  0.
 229 300 20.  0.
   5 100  2.  3.9
  43 100  5.  3.9
  76 100 10.  3.9
   4 100  2.  19.5
  57 100  5.  19.5
  83 100 10.  19.5
   6 100  2.  39.
  57 100  5.  39.
  84 100 10.  39.
7


28
**** problem mn205.1 ****
10
-
 Example on p. 205-6 of McCullagh and Nelder
  15   5  10   2   7   6   6
 -2.896,1.345,1.708,1.674,1.98
 (1X,F3.0,F4.0,F4.0,F6.2)
   7 100  4.  0.
  59 200  5.  0.
 115 300  8.  0.
 149 300 10.  0.
 178 300 15.  0.
 229 300 20.  0.
   5 100  2.  3.9
  43 100  5.  3.9
  76 100 10.  3.9
   4 100  2.  19.5
  57 100  5.  19.5
  83 100 10.  19.5
   6 100  2.  39.
  57 100  5.  39.
  84 100 10.  39.
7


28
**** problem speed ****
10
-
Speed data from Daryl(14.2): E(y)=b*x+c*x^2, var(y) = phi*E(y)^theta
  50   4   1   2  11   6   6   2
1.        0.
 (1X,2F3.0,4X,F5.0,F8.0)
   2  1  1.   4.     16.
  10  1  1.   4.     16.
   4  1  1.   7.     49.
  22  1  1.   7.     49.
  16  1  1.   8.     64.
  10  1  1.   9.     81.
  18  1  1.  10.    100.
  26  1  1.  10.    100.
  34  1  1.  10.    100.
  17  1  1.  11.    121.
  28  1  1.  11.    121.
  14  1  1.  12.    144.
  20  1  1.  12.    144.
  24  1  1.  12.    144.
  28  1  1.  12.    144.
  26  1  1.  13.    169.
  34  1  1.  13.    169.
  34  1  1.  13.    169.
  46  1  1.  13.    169.
  26  1  1.  14.    196.
  36  1  1.  14.    196.
  60  1  1.  14.    196.
  80  1  1.  14.    196.
  20  1  1.  15.    225.
  26  1  1.  15.    225.
  54  1  1.  15.    225.
  32  1  1.  16.    256.
  40  1  1.  16.    256.
  32  1  1.  17.    289.
  40  1  1.  17.    289.
  50  1  1.  17.    289.
  42  1  1.  18.    324.
  56  1  1.  18.    324.
  76  1  1.  18.    324.
  84  1  1.  18.    324.
  36  1  1.  19.    361.
  46  1  1.  19.    361.
  68  1  1.  19.    361.
  32  1  1.  20.    400.
  48  1  1.  20.    400.
  52  1  1.  20.    400.
  56  1  1.  20.    400.
  64  1  1.  20.    400.
  66  1  1.  22.    484.
  54  1  1.  23.    529.
  70  1  1.  24.    576.
  92  1  1.  24.    576.
  93  1  1.  24.    576.
 120  1  1.  24.    576.
  85  1  1.  25.    625.
7


28
**** problem textile ****
10
-
textile data from Daryl: E(y) = exp(b0+x1*b1+x2*b2+x3*b3), Var(y) = mu^theta
  27   6   2   4  11   6   6   4
1.        0.
 (F4.0,F2.0,4F5.0)
 674 1   1.  -1.  -1.  -1.
 370 1   1.  -1.  -1.   0.
 292 1   1.  -1.  -1.   1.
 338 1   1.  -1.   0.  -1.
 266 1   1.  -1.   0.   0.
 210 1   1.  -1.   0.   1.
 170 1   1.  -1.   1.  -1.
 118 1   1.  -1.   1.   0.
  90 1   1.  -1.   1.   1.
1414 1   1.   0.  -1.  -1.
1198 1   1.   0.  -1.   0.
 634 1   1.   0.  -1.   1.
1022 1   1.   0.   0.  -1.
 620 1   1.   0.   0.   0.
 438 1   1.   0.   0.   1.
 442 1   1.   0.   1.  -1.
 332 1   1.   0.   1.   0.
 220 1   1.   0.   1.   1.
3636 1   1.   1.  -1.  -1.
3184 1   1.   1.  -1.   0.
2000 1   1.   1.  -1.   1.
1568 1   1.   1.   0.  -1.
1070 1   1.   1.   0.   0.
 566 1   1.   1.   0.   1.
1140 1   1.   1.   1.  -1.
 884 1   1.   1.   1.   0.
 360 1   1.   1.   1.   1.
7


28
**** problem insurance (D = I) ****
10
-
Insurance data from Daryl.
 123  17   1  14  11   6   6  14
1.        0.        1.
 (16F4.0)
 289   8   1   0   0   0   0   0   0   1   0   0   1   0   0   1
 372  10   1   0   0   0   0   0   0   0   1   0   1   0   0   1
 189   9   1   0   0   0   0   0   0   0   0   1   1   0   0   1
 763   3   1   0   0   0   0   0   0  -1  -1  -1   1   0   0   1
 302  18   0   1   0   0   0   0   0   1   0   0   1   0   0   1
 420  59   0   1   0   0   0   0   0   0   1   0   1   0   0   1
 268  44   0   1   0   0   0   0   0   0   0   1   1   0   0   1
 407  24   0   1   0   0   0   0   0  -1  -1  -1   1   0   0   1
 268  56   0   0   1   0   0   0   0   1   0   0   1   0   0   1
 275 125   0   0   1   0   0   0   0   0   1   0   1   0   0   1
 334 163   0   0   1   0   0   0   0   0   0   1   1   0   0   1
 383  72   0   0   1   0   0   0   0  -1  -1  -1   1   0   0   1
 236  43   0   0   0   1   0   0   0   1   0   0   1   0   0   1
 259 179   0   0   0   1   0   0   0   0   1   0   1   0   0   1
 340 197   0   0   0   1   0   0   0   0   0   1   1   0   0   1
 400 104   0   0   0   1   0   0   0  -1  -1  -1   1   0   0   1
 207  43   0   0   0   0   1   0   0   1   0   0   1   0   0   1
 208 191   0   0   0   0   1   0   0   0   1   0   1   0   0   1
 251 210   0   0   0   0   1   0   0   0   0   1   1   0   0   1
 233 119   0   0   0   0   1   0   0  -1  -1  -1   1   0   0   1
 254  90   0   0   0   0   0   1   0   1   0   0   1   0   0   1
 218 380   0   0   0   0   0   1   0   0   1   0   1   0   0   1
 239 401   0   0   0   0   0   1   0   0   0   1   1   0   0   1
 387 199   0   0   0   0   0   1   0  -1  -1  -1   1   0   0   1
 251  69   0   0   0   0   0   0   1   1   0   0   1   0   0   1
 196 366   0   0   0   0   0   0   1   0   1   0   1   0   0   1
 268 310   0   0   0   0   0   0   1   0   0   1   1   0   0   1
 391 105   0   0   0   0   0   0   1  -1  -1  -1   1   0   0   1
 264  64  -1  -1  -1  -1  -1  -1  -1   1   0   0   1   0   0   1
 224 228  -1  -1  -1  -1  -1  -1  -1   0   1   0   1   0   0   1
 269 183  -1  -1  -1  -1  -1  -1  -1   0   0   1   1   0   0   1
 385  62  -1  -1  -1  -1  -1  -1  -1  -1  -1  -1   1   0   0   1
 282   8   1   0   0   0   0   0   0   1   0   0   0   1   0   1
 249  28   1   0   0   0   0   0   0   0   1   0   0   1   0   1
 288  13   1   0   0   0   0   0   0   0   0   1   0   1   0   1
 850   2   1   0   0   0   0   0   0  -1  -1  -1   0   1   0   1
 194  31   0   1   0   0   0   0   0   1   0   0   0   1   0   1
 243  96   0   1   0   0   0   0   0   0   1   0   0   1   0   1
 343  39   0   1   0   0   0   0   0   0   0   1   0   1   0   1
 320  18   0   1   0   0   0   0   0  -1  -1  -1   0   1   0   1
 285  55   0   0   1   0   0   0   0   1   0   0   0   1   0   1
 243 172   0   0   1   0   0   0   0   0   1   0   0   1   0   1
 274 129   0   0   1   0   0   0   0   0   0   1   0   1   0   1
 305  50   0   0   1   0   0   0   0  -1  -1  -1   0   1   0   1
 270  53   0   0   0   1   0   0   0   1   0   0   0   1   0   1
 226 211   0   0   0   1   0   0   0   0   1   0   0   1   0   1
 260 125   0   0   0   1   0   0   0   0   0   1   0   1   0   1
 349  55   0   0   0   1   0   0   0  -1  -1  -1   0   1   0   1
 129  73   0   0   0   0   1   0   0   1   0   0   0   1   0   1
 214 219   0   0   0   0   1   0   0   0   1   0   0   1   0   1
 232 131   0   0   0   0   1   0   0   0   0   1   0   1   0   1
 325  43   0   0   0   0   1   0   0  -1  -1  -1   0   1   0   1
 213  98   0   0   0   0   0   1   0   1   0   0   0   1   0   1
 209 434   0   0   0   0   0   1   0   0   1   0   0   1   0   1
 250 253   0   0   0   0   0   1   0   0   0   1   0   1   0   1
 299  88   0   0   0   0   0   1   0  -1  -1  -1   0   1   0   1
 227 120   0   0   0   0   0   0   1   1   0   0   0   1   0   1
 229 353   0   0   0   0   0   0   1   0   1   0   0   1   0   1
 250 148   0   0   0   0   0   0   1   0   0   1   0   1   0   1
 228  46   0   0   0   0   0   0   1  -1  -1  -1   0   1   0   1
 198 100  -1  -1  -1  -1  -1  -1  -1   1   0   0   0   1   0   1
 193 233  -1  -1  -1  -1  -1  -1  -1   0   1   0   0   1   0   1
 258 103  -1  -1  -1  -1  -1  -1  -1   0   0   1   0   1   0   1
 324  22  -1  -1  -1  -1  -1  -1  -1  -1  -1  -1   0   1   0   1
 133   4   1   0   0   0   0   0   0   1   0   0   0   0   1   1
 288   1   1   0   0   0   0   0   0   0   1   0   0   0   1   1
 179   1   1   0   0   0   0   0   0   0   0   1   0   0   1   1
 135  10   0   1   0   0   0   0   0   1   0   0   0   0   1   1
 196  13   0   1   0   0   0   0   0   0   1   0   0   0   1   1
 293   7   0   1   0   0   0   0   0   0   0   1   0   0   1   1
 205   2   0   1   0   0   0   0   0  -1  -1  -1   0   0   1   1
 181  17   0   0   1   0   0   0   0   1   0   0   0   0   1   1
 179  36   0   0   1   0   0   0   0   0   1   0   0   0   1   1
 208  18   0   0   1   0   0   0   0   0   0   1   0   0   1   1
 116   6   0   0   1   0   0   0   0  -1  -1  -1   0   0   1   1
 160  15   0   0   0   1   0   0   0   1   0   0   0   0   1   1
 161  39   0   0   0   1   0   0   0   0   1   0   0   0   1   1
 189  30   0   0   0   1   0   0   0   0   0   1   0   0   1   1
 147   8   0   0   0   1   0   0   0  -1  -1  -1   0   0   1   1
 157  21   0   0   0   0   1   0   0   1   0   0   0   0   1   1
 149  46   0   0   0   0   1   0   0   0   1   0   0   0   1   1
 204  32   0   0   0   0   1   0   0   0   0   1   0   0   1   1
 207   4   0   0   0   0   1   0   0  -1  -1  -1   0   0   1   1
 149  35   0   0   0   0   0   1   0   1   0   0   0   0   1   1
 172  97   0   0   0   0   0   1   0   0   1   0   0   0   1   1
 174  50   0   0   0   0   0   1   0   0   0   1   0   0   1   1
 325   8   0   0   0   0   0   1   0  -1  -1  -1   0   0   1   1
 172  42   0   0   0   0   0   0   1   1   0   0   0   0   1   1
 164  95   0   0   0   0   0   0   1   0   1   0   0   0   1   1
 175  33   0   0   0   0   0   0   1   0   0   1   0   0   1   1
 346  10   0   0   0   0   0   0   1  -1  -1  -1   0   0   1   1
 167  43  -1  -1  -1  -1  -1  -1  -1   1   0   0   0   0   1   1
 178  73  -1  -1  -1  -1  -1  -1  -1   0   1   0   0   0   1   1
 227  20  -1  -1  -1  -1  -1  -1  -1   0   0   1   0   0   1   1
 192   6  -1  -1  -1  -1  -1  -1  -1  -1  -1  -1   0   0   1   1
 160   1   1   0   0   0   0   0   0   1   0   0  -1  -1  -1   1
  11   1   1   0   0   0   0   0   0   0   1   0  -1  -1  -1   1
 166   4   0   1   0   0   0   0   0   1   0   0  -1  -1  -1   1
 135   3   0   1   0   0   0   0   0   0   1   0  -1  -1  -1   1
 104   2   0   1   0   0   0   0   0   0   0   1  -1  -1  -1   1
 110  12   0   0   1   0   0   0   0   1   0   0  -1  -1  -1   1
 264  10   0   0   1   0   0   0   0   0   1   0  -1  -1  -1   1
 150   8   0   0   1   0   0   0   0   0   0   1  -1  -1  -1   1
 636   1   0   0   1   0   0   0   0  -1  -1  -1  -1  -1  -1   1
 110  12   0   0   0   1   0   0   0   1   0   0  -1  -1  -1   1
 107  19   0   0   0   1   0   0   0   0   1   0  -1  -1  -1   1
 104   9   0   0   0   1   0   0   0   0   0   1  -1  -1  -1   1
  65   2   0   0   0   1   0   0   0  -1  -1  -1  -1  -1  -1   1
 113  14   0   0   0   0   1   0   0   1   0   0  -1  -1  -1   1
 137  23   0   0   0   0   1   0   0   0   1   0  -1  -1  -1   1
 141   8   0   0   0   0   1   0   0   0   0   1  -1  -1  -1   1
  98  22   0   0   0   0   0   1   0   1   0   0  -1  -1  -1   1
 110  59   0   0   0   0   0   1   0   0   1   0  -1  -1  -1   1
 129  15   0   0   0   0   0   1   0   0   0   1  -1  -1  -1   1
 137   9   0   0   0   0   0   1   0  -1  -1  -1  -1  -1  -1   1
  98  35   0   0   0   0   0   0   1   1   0   0  -1  -1  -1   1
 132  45   0   0   0   0   0   0   1   0   1   0  -1  -1  -1   1
 152  13   0   0   0   0   0   0   1   0   0   1  -1  -1  -1   1
 167   1   0   0   0   0   0   0   1  -1  -1  -1  -1  -1  -1   1
 114  53  -1  -1  -1  -1  -1  -1  -1   1   0   0  -1  -1  -1   1
 101  44  -1  -1  -1  -1  -1  -1  -1   0   1   0  -1  -1  -1   1
 119   6  -1  -1  -1  -1  -1  -1  -1   0   0   1  -1  -1  -1   1
 123   6  -1  -1  -1  -1  -1  -1  -1  -1  -1  -1  -1  -1  -1   1
2
16,0
0,0
3
38,1.
0,0
5
0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,2,-1
11
13
7


28
**** problem insurance.1 (D = I) ****
5
0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1.5,-1
7
