# hs105.mod OBR2-RN-8-16 # Original AMPL coding by Elena Bobrovnikova (summer 1996 at Bell Labs). # Maximum likelihood estimation # Ref.: W. Hock and K. Schittkowski, Test Examples for Nonlinear Programming # Codes. Lecture Notes in Economics and Mathematical Systems, v. 187, # Springer-Verlag, New York, 1981, p. 114. # Number of variables: 8 # Number of constraints: 16 (17 before presolve) # Objective nonseparable # Objective nonconvex # Linear constraints set I := 1 .. 235; param PI := 4*atan(1); param y{I}; var x{1..8}; var a{i in I} = x[1] / x[6] * exp(-(y[i] - x[3])^2 / (2 * x[6]^2)); var b{i in I} = x[2] / x[7] * exp(-(y[i] - x[4])^2 / (2 * x[7]^2)); var c{i in I} = (1 - x[2] - x[1]) / x[8] * exp(-(y[i] - x[5])^2 / (2 * x[8]^2)); minimize f: - sum {i in I} log((a[i] + b[i] + c[i]) / sqrt(2 * PI)); s.t. C1: 1 - x[1] - x[2] >= 0; s.t. B12{i in 1..2}: .001 <= x[i] <= .499; s.t. B3: 100 <= x[3] <= 180; s.t. B4: 130 <= x[4] <= 210; s.t. B5: 170 <= x[5] <= 240; s.t. B678{i in 6..8}: 5 <= x[i] <= 25; data; param y := 1 95 61 135 121 155 181 180 2 105 62 135 122 155 182 185 3 110 63 135 123 160 183 185 4 110 64 135 124 160 184 185 5 110 65 135 125 160 185 185 6 110 66 135 126 160 186 185 7 115 67 135 127 160 187 185 8 115 68 135 128 160 188 190 9 115 69 140 129 160 189 190 10 115 70 140 130 160 190 190 11 120 71 140 131 160 191 190 12 120 72 140 132 160 192 190 13 120 73 140 133 160 193 190 14 120 74 140 134 160 194 190 15 120 75 140 135 160 195 195 16 120 76 140 136 160 196 195 17 120 77 140 137 160 197 195 18 120 78 140 138 160 198 195 19 120 79 140 139 160 199 200 20 120 80 140 140 160 200 200 21 120 81 140 141 160 201 200 22 120 82 140 142 160 202 205 23 120 83 140 143 165 203 205 24 120 84 140 144 165 204 205 25 120 85 140 145 165 205 210 26 125 86 140 146 165 206 210 27 125 87 140 147 165 207 210 28 125 88 140 148 165 208 210 29 125 89 140 149 165 209 210 30 125 90 145 150 165 210 210 31 125 91 145 151 170 211 210 32 125 92 145 152 170 212 210 33 125 93 145 153 170 213 215 34 125 94 145 154 170 214 220 35 125 95 145 155 170 215 220 36 125 96 145 156 170 216 220 37 125 97 145 157 170 217 220 38 125 98 145 158 170 218 220 39 125 99 145 159 170 219 220 40 125 100 145 160 170 220 230 41 130 101 145 161 170 221 230 42 130 102 150 162 170 222 230 43 130 103 150 163 170 223 230 44 130 104 150 164 170 224 230 45 130 105 150 165 170 225 235 46 130 106 150 166 170 226 240 47 130 107 150 167 170 227 240 48 130 108 150 168 175 228 240 49 130 109 150 169 175 229 240 50 130 110 150 170 175 230 240 51 130 111 150 171 175 231 240 52 130 112 150 172 175 232 240 53 130 113 150 173 175 233 245 54 130 114 150 174 175 234 250 55 130 115 150 175 175 235 250 56 135 116 150 176 180 57 135 117 150 177 180 58 135 118 150 178 180 59 135 119 155 179 180 60 135 120 155 180 180 ; var x := 1 .1 2 .2 3 100 4 125 5 175 6 11.2 7 13.2 8 15.8 ;