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