Starting preprocessing of the model file ... Found 44 equation(s). Evaluating expressions...done Computing static model derivatives (order 1). Computing dynamic model derivatives (order 2). Processing outputs ... done Preprocessing completed. Residuals of the static equations: Equation number 1 : 0 : c1 Equation number 2 : 0 : c2 Equation number 3 : 0 : 3 Equation number 4 : 0 : c Equation number 5 : 0 : n Equation number 6 : 0 : y Equation number 7 : 0 : 7 Equation number 8 : 0 : 8 Equation number 9 : 0 : pi_h Equation number 10 : 0 : mc_h Equation number 11 : 0 : pi_f Equation number 12 : 0 : pi Equation number 13 : 0 : 13 Equation number 14 : 0 : mrs_w Equation number 15 : 0 : mrs_w1 Equation number 16 : 0 : mrs_w2 Equation number 17 : 0 : pi_w Equation number 18 : 0 : 18 Equation number 19 : 0 : i Equation number 20 : 0 : r Equation number 21 : 0 : q Equation number 22 : 0 : 22 Equation number 23 : 0 : 23 Equation number 24 : 0 : y_star Equation number 25 : 0 : pi_star Equation number 26 : 0 : i_star Equation number 27 : 0 : z Equation number 28 : 0 : mu_c Equation number 29 : 0 : mu_h Equation number 30 : 0 : mu_f Equation number 31 : 0 : mu_w Equation number 32 : 0 : mu_d Equation number 33 : 0 : mu_i Equation number 34 : 0 : d_z Equation number 35 : 0 : d_y Equation number 36 : 0 : y_obs Equation number 37 : 0 : pi_obs Equation number 38 : 0 : i_obs Equation number 39 : 0 : d_obs Equation number 40 : 0 : d_y_star Equation number 41 : 0 : d_pi_star Equation number 42 : 0 : y_star_obs Equation number 43 : 0 : pi_star_obs Equation number 44 : 0 : i_star_obs STEADY-STATE RESULTS: y 0 c 0 c1 0 c2 0 n1 0 n2 0 n 0 a 0 pi_h 0 mc_h 0 pi_f 0 pi_w 0 mrs_w 0 mrs_w1 0 mrs_w2 0 pi 0 w 0 psi 0 s 0 q 0 d 0 i 0 r 0 y_star 0 pi_star 0 i_star 0 z 0 mu_c 0 mu_h 0 mu_f 0 mu_w 0 mu_d 0 mu_i 0 d_y 0 d_y_star 0 d_pi_star 0 d_z 0 y_obs 0 pi_obs 0 i_obs 0 d_obs 0 y_star_obs 0 pi_star_obs 0 i_star_obs 0 EIGENVALUES: Modulus Real Imaginary 1.087e-17 1.087e-17 0 2.964e-17 -2.964e-17 0 0.2982 0.2982 0 0.5462 0.4481 0.3123 0.5462 0.4481 -0.3123 0.5601 0.5601 0 0.6 0.6 0 0.6 0.6 0 0.6 0.6 0 0.6 0.6 0 0.6 0.6 0 0.6 0.6 0 0.6 0.6 0 0.6 0.6 0 0.6 0.6 0 0.6 0.6 0 0.6056 0.5414 0.2713 0.6056 0.5414 -0.2713 0.6602 0.6602 0 0.9531 0.9531 0 1.051 1.051 0 1.494 1.416 0.4752 1.494 1.416 -0.4752 2.063 2.058 0.1482 2.063 2.058 -0.1482 3.753e+16 -3.753e+16 0 There are 6 eigenvalue(s) larger than 1 in modulus for 6 forward-looking variable(s) The rank condition is verified. PARAMETER INITIALIZATION: Some standard deviations of shocks of the calibrated model are 0 and PARAMETER INITIALIZATION: violate the inverse gamma prior. They will instead be initialized with the prior mean. PARAMETER INITIALIZATION: Some measurement errors of the calibrated model are 0 and violate the PARAMETER INITIALIZATION: inverse gamma prior. They will instead be initialized with the prior mean. Initial value of the log posterior (or likelihood): 593.9425 ----------------- f at the beginning of new iteration, -593.9425448892 Predicted improvement: 322394.997710406 lambda = 1; f = -593.9108888 lambda = 0.33333; f = -593.9395730 lambda = 0.11111; f = -593.9423565 lambda = 0.037037; f = -593.9425440 lambda = 0.012346; f = -792.4859165 lambda = 0.0041152; f = -880.9815140 lambda = 0.0013717; f = -855.1916072 lambda = 0.00045725; f = -761.9519652 Norm of dx 8.0299 ---- Improvement on iteration 1 = 287.038969106 ----------------- f at the beginning of new iteration, -880.9815139947 Predicted improvement: 5641.605234886 lambda = 1; f = -880.2938486 lambda = 0.33333; f = -880.9101197 lambda = 0.11111; f = -880.9750176 lambda = 0.037037; f = -880.9811171 lambda = 0.012346; f = -880.9815105 lambda = 0.0041152; f = -927.9079501 lambda = 0.0079555; f = -956.3941659 lambda = 0.015379; f = -880.9814984 lambda = 0.010356; f = -880.9815137 lambda = 0.008168; f = -948.0468622 lambda = 0.0094179; f = -880.9815140 lambda = 0.0086467; f = -880.7458320 lambda = 0.0082147; f = -945.2777987 Norm of dx 1.0714 ---- Improvement on iteration 2 = 75.412651868 warning: possible inaccuracy in H matrix ----------------- f at the beginning of new iteration, -956.3941658629 Predicted improvement: 12091.822055645 lambda = 1; f = -952.5631229 lambda = 0.33333; f = -955.9763977 lambda = 0.11111; f = -956.3502120 lambda = 0.037037; f = -956.3899522 lambda = 0.012346; f = -956.3938397 lambda = 0.0041152; f = -956.3941442 lambda = 0.0013717; f = -956.3941651 lambda = 0.00045725; f = -904.1515259 lambda = 0.00015242; f = -957.7512037 Norm of dx 2.754 ---- Improvement on iteration 3 = 1.357037861 ----------------- f at the beginning of new iteration, -957.7512037240 Predicted improvement: 8589.108491303 lambda = 1; f = -955.7630331 lambda = 0.33333; f = -957.5375071 lambda = 0.11111; f = -957.7296973 lambda = 0.037037; f = -957.7494139 lambda = 0.012346; f = -957.7511246 lambda = 0.0041152; f = -957.7512028 lambda = 0.0013717; f = -959.8666205 lambda = 0.00045725; f = -962.9973816 Norm of dx 2.3302 ---- Improvement on iteration 4 = 5.246177835 ----------------- f at the beginning of new iteration, -962.9973815586 Predicted improvement: 1459.788990818 lambda = 1; f = -962.8314083 lambda = 0.33333; f = -962.9809411 lambda = 0.11111; f = -962.9960890 lambda = 0.037037; f = -962.9973370 lambda = 0.012346; f = -931.8129135 lambda = 0.0041152; f = -969.1996211 Norm of dx 0.6641 ---- Improvement on iteration 5 = 6.202239545 ----------------- f at the beginning of new iteration, -969.1996211035 Predicted improvement: 426.648200003 lambda = 1; f = -969.1255835 lambda = 0.33333; f = -969.1923730 lambda = 0.11111; f = -969.1990312 lambda = 0.037037; f = -969.1995917 lambda = 0.012346; f = -969.1996210 lambda = 0.0041152; f = -972.3036273 lambda = 0.0079555; f = -971.1879612 lambda = 0.0053568; f = -972.9334780 lambda = 0.0067914; f = -973.0114097 Norm of dx 0.34836 ---- Improvement on iteration 6 = 3.811788549 ----------------- f at the beginning of new iteration, -973.0114096525 Predicted improvement: 404.973465999 lambda = 1; f = -972.9173758 lambda = 0.33333; f = -973.0020170 lambda = 0.11111; f = -973.0106135 lambda = 0.037037; f = -973.0113582 lambda = 0.012346; f = -973.0114081 lambda = 0.0041152; f = -974.0698177 Norm of dx 0.42809 ---- Improvement on iteration 7 = 1.058408005 ----------------- f at the beginning of new iteration, -974.0698176577 Predicted improvement: 256.963755600 lambda = 1; f = -974.0384006 lambda = 0.33333; f = -974.0672123 lambda = 0.11111; f = -974.0696851 lambda = 0.037037; f = -974.0698172 lambda = 0.012346; f = -977.5167827 Norm of dx 0.33993 ---- Improvement on iteration 8 = 3.446965036 ----------------- f at the beginning of new iteration, -977.5167826936 Predicted improvement: 1047.676016848 lambda = 1; f = -976.6991459 lambda = 0.33333; f = -977.4571361 lambda = 0.11111; f = -977.5115647 lambda = 0.037037; f = -977.5164088 lambda = 0.012346; f = -977.5167746 lambda = 0.0041152; f = -972.4043171 lambda = 0.0013717; f = -979.3850515 Norm of dx 1.4435 ---- Improvement on iteration 9 = 1.868268790 ----------------- f at the beginning of new iteration, -979.3850514836 Predicted improvement: 889.343291040 lambda = 1; f = -978.7488786 lambda = 0.33333; f = -979.3398630 lambda = 0.11111; f = -979.3812134 lambda = 0.037037; f = -979.3847770 lambda = 0.012346; f = -979.3850448 lambda = 0.0041152; f = -978.3456952 lambda = 0.0013717; f = -981.3795660 lambda = 0.0026518; f = -982.0771088 Norm of dx 1.2767 ---- Improvement on iteration 10 = 2.692057312 ----------------- f at the beginning of new iteration, -982.0771087951 Predicted improvement: 408.381668218 lambda = 1; f = -981.9922417 lambda = 0.33333; f = -982.0708869 lambda = 0.11111; f = -982.0766438 lambda = 0.037037; f = -982.0770890 lambda = 0.012346; f = -948.7248663 lambda = 0.0041152; f = -984.8444050 lambda = 0.0079555; f = -985.2737864 Norm of dx 0.63488 ---- Improvement on iteration 11 = 3.196677601 ----------------- f at the beginning of new iteration, -985.2737863960 Predicted improvement: 503.664056659 lambda = 1; f = -985.1285036 lambda = 0.33333; f = -985.2677557 lambda = 0.11111; f = -985.2734800 lambda = 0.037037; f = -985.2737762 lambda = 0.012346; f = -990.9900945 Norm of dx 0.82129 ---- Improvement on iteration 12 = 5.716308095 ----------------- f at the beginning of new iteration, -990.9900944910 Predicted improvement: 296.319930009 lambda = 1; f = -990.9650792 lambda = 0.33333; f = -990.9895528 lambda = 0.11111; f = -990.9900943 lambda = 0.037037; f = -991.8947034 lambda = 0.012346; f = -994.0326340 Norm of dx 0.5235 ---- Improvement on iteration 13 = 3.042539535 ----------------- f at the beginning of new iteration, -994.0326340261 Predicted improvement: 59.286140491 lambda = 1; f = -994.0323892 lambda = 0.33333; f = -874.7686224 lambda = 0.11111; f = -1001.6585452 Norm of dx 0.15458 ---- Improvement on iteration 14 = 7.625911209 ----------------- f at the beginning of new iteration, -1001.6585452355 Predicted improvement: 1061.948241036 lambda = 1; f = -996.1007379 lambda = 0.33333; f = -1001.2775159 lambda = 0.11111; f = -1001.6537202 lambda = 0.037037; f = -1001.6585201 lambda = 0.012346; f = -998.9720451 lambda = 0.0041152; f = -1007.6811809 Norm of dx 2.8116 ---- Improvement on iteration 15 = 6.022635683 ----------------- f at the beginning of new iteration, -1007.6811809181 Predicted improvement: 624.813470260 lambda = 1; f = -1005.8955758 lambda = 0.33333; f = -1007.5986564 lambda = 0.11111; f = -1007.6800368 lambda = 0.037037; f = -1007.6811793 lambda = 0.012346; f = -1010.0365574 lambda = 0.0041152; f = -1011.2854888 lambda = 0.0079555; f = -1012.1864009 Norm of dx 1.6992 ---- Improvement on iteration 16 = 4.505219935 ----------------- f at the beginning of new iteration, -1012.1864008529 Predicted improvement: 92.371713128 lambda = 1; f = -1012.1774835 lambda = 0.33333; f = -1012.1859647 lambda = 0.11111; f = -590.3436462 lambda = 0.037037; f = -1014.4931383 Norm of dx 0.28654 ---- Improvement on iteration 17 = 2.306737433 ----------------- f at the beginning of new iteration, -1014.4931382856 Predicted improvement: 325.444031449 lambda = 1; f = -1013.9068250 lambda = 0.33333; f = -1014.4747428 lambda = 0.11111; f = -1014.4920941 lambda = 0.037037; f = -1014.4931202 lambda = 0.012346; f = -1021.1972199 lambda = 0.023866; f = -1014.4007193 lambda = 0.01607; f = -1022.7655628 lambda = 0.020374; f = -1023.8955497 lambda = 0.025831; f = -1014.4931383 lambda = 0.022403; f = -1022.5828299 Norm of dx 1.0325 ---- Improvement on iteration 18 = 9.402411422 warning: possible inaccuracy in H matrix ----------------- f at the beginning of new iteration, -1023.8955497080 Predicted improvement: 22.807941420 lambda = 1; f = -988.9442286 lambda = 0.33333; f = -1025.8402995 lambda = 0.11111; f = -1026.1408708 Norm of dx 0.081491 ---- Improvement on iteration 19 = 2.245321097 ----------------- f at the beginning of new iteration, -1026.1408708046 Predicted improvement: 5.734560831 lambda = 1; f = -1030.3783333 Norm of dx 0.032482 ---- Improvement on iteration 20 = 4.237462452 ----------------- f at the beginning of new iteration, -1030.3783332571 Predicted improvement: 3.991314867 lambda = 1; f = -1035.1779325 Norm of dx 0.018608 ---- Improvement on iteration 21 = 4.799599234 ----------------- f at the beginning of new iteration, -1035.1779324915 Predicted improvement: 8.143011381 lambda = 1; f = -1031.4983993 lambda = 0.33333; f = -1038.1728452 Norm of dx 0.062949 ---- Improvement on iteration 22 = 2.994912675 ----------------- f at the beginning of new iteration, -1038.1728451667 Predicted improvement: 3.911827845 lambda = 1; f = -1043.3493061 Norm of dx 0.052856 ---- Improvement on iteration 23 = 5.176460917 ----------------- f at the beginning of new iteration, -1043.3493060841 Predicted improvement: 4.582527473 lambda = 1; f = -1050.6992616 lambda = 1.9332; f = -1054.9504460 Norm of dx 0.074184 ---- Improvement on iteration 24 = 11.601139954 ----------------- f at the beginning of new iteration, -1054.9504460382 Predicted improvement: 6.478872479 lambda = 1; f = -1052.4259043 lambda = 0.33333; f = -1058.0162698 lambda = 0.64439; f = -1057.8449665 Norm of dx 0.13618 ---- Improvement on iteration 25 = 3.065823717 ----------------- f at the beginning of new iteration, -1058.0162697553 Predicted improvement: 3.471404319 lambda = 1; f = -1062.7436830 Norm of dx 0.054996 ---- Improvement on iteration 26 = 4.727413293 ----------------- f at the beginning of new iteration, -1062.7436830483 Predicted improvement: 2.876084538 lambda = 1; f = -1066.0954401 Norm of dx 0.0487 ---- Improvement on iteration 27 = 3.351757057 ----------------- f at the beginning of new iteration, -1066.0954401050 Predicted improvement: 5.002636942 lambda = 1; f = -1066.0954401 lambda = 0.33333; f = -1067.8667123 Norm of dx 0.11849 ---- Improvement on iteration 28 = 1.771272227 ----------------- f at the beginning of new iteration, -1067.8667123322 Predicted improvement: 5.803337441 lambda = 1; f = -1070.8051662 lambda = 0.33333; f = -1070.4519924 Norm of dx 0.084871 ---- Improvement on iteration 29 = 2.938453863 ----------------- f at the beginning of new iteration, -1070.8051661949 Predicted improvement: 6.756232887 lambda = 1; f = -1070.8051573 lambda = 0.33333; f = -1075.4478419 lambda = 0.64439; f = -818.3575104 lambda = 0.4339; f = -1076.9874365 lambda = 0.55011; f = -1078.5159225 lambda = 0.69744; f = -1070.8051660 lambda = 0.60488; f = -1074.9918668 Norm of dx 0.06591 ---- Improvement on iteration 30 = 7.710756272 warning: possible inaccuracy in H matrix ----------------- f at the beginning of new iteration, -1078.5159224666 Predicted improvement: 6.635278036 lambda = 1; f = -1074.4326175 lambda = 0.33333; f = -1077.9368399 lambda = 0.11111; f = -1078.4856487 lambda = 0.037037; f = -1078.6808742 Norm of dx 0.076724 ---- Improvement on iteration 31 = 0.164951771 ----------------- f at the beginning of new iteration, -1078.6808742372 Predicted improvement: 9.292640078 lambda = 1; f = -1074.5405677 lambda = 0.33333; f = -1082.6596517 Norm of dx 0.077503 ---- Improvement on iteration 32 = 3.978777509 ----------------- f at the beginning of new iteration, -1082.6596517461 Predicted improvement: 2.079962208 lambda = 1; f = -1084.6227682 Norm of dx 0.042301 ---- Improvement on iteration 33 = 1.963116437 ----------------- f at the beginning of new iteration, -1084.6227681831 Predicted improvement: 1.090824191 lambda = 1; f = -1086.0312935 Norm of dx 0.016732 ---- Improvement on iteration 34 = 1.408525320 ----------------- f at the beginning of new iteration, -1086.0312935031 Predicted improvement: 1.022318830 lambda = 1; f = -1087.2245282 Norm of dx 0.04885 ---- Improvement on iteration 35 = 1.193234699 ----------------- f at the beginning of new iteration, -1087.2245282023 Predicted improvement: 0.885264611 lambda = 1; f = -1088.0542360 Norm of dx 0.045973 ---- Improvement on iteration 36 = 0.829707800 ----------------- f at the beginning of new iteration, -1088.0542360026 Predicted improvement: 0.668370998 lambda = 1; f = -1089.1521637 lambda = 1.9332; f = -1089.7591531 Norm of dx 0.020771 ---- Improvement on iteration 37 = 1.704917131 ----------------- f at the beginning of new iteration, -1089.7591531340 Predicted improvement: 0.723341542 lambda = 1; f = -1090.6844471 Norm of dx 0.035594 ---- Improvement on iteration 38 = 0.925293937 ----------------- f at the beginning of new iteration, -1090.6844470709 Predicted improvement: 0.423243759 lambda = 1; f = -1091.2614387 Norm of dx 0.031153 ---- Improvement on iteration 39 = 0.576991611 ----------------- f at the beginning of new iteration, -1091.2614386822 Predicted improvement: 0.525533848 lambda = 1; f = -1091.9209491 Norm of dx 0.050001 ---- Improvement on iteration 40 = 0.659510368 ----------------- f at the beginning of new iteration, -1091.9209490503 Predicted improvement: 0.445087748 lambda = 1; f = -1092.4880877 Norm of dx 0.038164 ---- Improvement on iteration 41 = 0.567138640 ----------------- f at the beginning of new iteration, -1092.4880876898 Predicted improvement: 0.412500546 lambda = 1; f = -1093.1044805 lambda = 1.9332; f = -1093.2933192 Norm of dx 0.033883 ---- Improvement on iteration 42 = 0.805231490 ----------------- f at the beginning of new iteration, -1093.2933191797 Predicted improvement: 0.606334065 lambda = 1; f = -1094.1449305 lambda = 1.9332; f = -1094.3285952 Norm of dx 0.027946 ---- Improvement on iteration 43 = 1.035276002 ----------------- f at the beginning of new iteration, -1094.3285951812 Predicted improvement: 0.567506794 lambda = 1; f = -1095.1104261 Norm of dx 0.018725 ---- Improvement on iteration 44 = 0.781830932 ----------------- f at the beginning of new iteration, -1095.1104261130 Predicted improvement: 0.331962558 lambda = 1; f = -1095.5375183 Norm of dx 0.032701 ---- Improvement on iteration 45 = 0.427092149 ----------------- f at the beginning of new iteration, -1095.5375182619 Predicted improvement: 0.227111005 lambda = 1; f = -1095.8706905 lambda = 1.9332; f = -1095.8927638 Norm of dx 0.023986 ---- Improvement on iteration 46 = 0.355245529 ----------------- f at the beginning of new iteration, -1095.8927637914 Predicted improvement: 0.164331663 lambda = 1; f = -1096.0913861 Norm of dx 0.013058 ---- Improvement on iteration 47 = 0.198622343 ----------------- f at the beginning of new iteration, -1096.0913861347 Predicted improvement: 0.092709215 lambda = 1; f = -1096.2390311 lambda = 1.9332; f = -1096.3082369 Norm of dx 0.0072531 ---- Improvement on iteration 48 = 0.216850783 ----------------- f at the beginning of new iteration, -1096.3082369173 Predicted improvement: 0.123747968 lambda = 1; f = -1096.5210907 lambda = 1.9332; f = -1096.6580088 lambda = 3.7372; f = -1096.7583940 Norm of dx 0.018074 ---- Improvement on iteration 49 = 0.450157055 ----------------- f at the beginning of new iteration, -1096.7583939726 Predicted improvement: 0.236419208 lambda = 1; f = -1097.0729113 Norm of dx 0.020299 ---- Improvement on iteration 50 = 0.314517361 ----------------- f at the beginning of new iteration, -1097.0729113340 Predicted improvement: 0.164979055 lambda = 1; f = -1097.2541096 Norm of dx 0.022395 ---- Improvement on iteration 51 = 0.181198282 ----------------- f at the beginning of new iteration, -1097.2541096160 Predicted improvement: 0.056970015 lambda = 1; f = -1097.3483822 lambda = 1.9332; f = -1097.3999216 Norm of dx 0.010041 ---- Improvement on iteration 52 = 0.145811988 ----------------- f at the beginning of new iteration, -1097.3999216044 Predicted improvement: 0.085385233 lambda = 1; f = -1097.5126268 Norm of dx 0.010825 ---- Improvement on iteration 53 = 0.112705175 ----------------- f at the beginning of new iteration, -1097.5126267795 Predicted improvement: 0.045058579 lambda = 1; f = -1097.5725366 Norm of dx 0.0085497 ---- Improvement on iteration 54 = 0.059909812 ----------------- f at the beginning of new iteration, -1097.5725365911 Predicted improvement: 0.025298116 lambda = 1; f = -1097.6125504 lambda = 1.9332; f = -1097.6300631 Norm of dx 0.0054256 ---- Improvement on iteration 55 = 0.057526465 ----------------- f at the beginning of new iteration, -1097.6300630560 Predicted improvement: 0.030252499 lambda = 1; f = -1097.6841109 lambda = 1.9332; f = -1097.7222086 lambda = 3.7372; f = -1097.7621689 Norm of dx 0.0063617 ---- Improvement on iteration 56 = 0.132105852 ----------------- f at the beginning of new iteration, -1097.7621689078 Predicted improvement: 0.048210352 lambda = 1; f = -1097.8412424 lambda = 1.9332; f = -1097.8836882 Norm of dx 0.01034 ---- Improvement on iteration 57 = 0.121519269 ----------------- f at the beginning of new iteration, -1097.8836881765 Correct for low angle: 0.00420305 Predicted improvement: 0.069177583 lambda = 1; f = -1097.9804831 Norm of dx 0.017185 ---- Improvement on iteration 58 = 0.096794922 ----------------- f at the beginning of new iteration, -1097.9804830990 Predicted improvement: 0.045040891 lambda = 1; f = -1098.0395501 Norm of dx 0.017149 ---- Improvement on iteration 59 = 0.059067011 ----------------- f at the beginning of new iteration, -1098.0395501098 Predicted improvement: 0.022066393 lambda = 1; f = -1098.0731181 lambda = 1.9332; f = -1098.0855114 Norm of dx 0.010266 ---- Improvement on iteration 60 = 0.045961256 ----------------- f at the beginning of new iteration, -1098.0855113657 Predicted improvement: 0.018869393 lambda = 1; f = -1098.1191656 lambda = 1.9332; f = -1098.1428523 lambda = 3.7372; f = -1098.1676701 Norm of dx 0.0040702 ---- Improvement on iteration 61 = 0.082158710 ----------------- f at the beginning of new iteration, -1098.1676700753 Predicted improvement: 0.028669370 lambda = 1; f = -1098.2067915 Norm of dx 0.008609 ---- Improvement on iteration 62 = 0.039121382 ----------------- f at the beginning of new iteration, -1098.2067914574 Predicted improvement: 0.021874692 lambda = 1; f = -1098.2373952 Norm of dx 0.0089647 ---- Improvement on iteration 63 = 0.030603775 ----------------- f at the beginning of new iteration, -1098.2373952320 Predicted improvement: 0.016152935 lambda = 1; f = -1098.2600056 Norm of dx 0.0092671 ---- Improvement on iteration 64 = 0.022610380 ----------------- f at the beginning of new iteration, -1098.2600056121 Predicted improvement: 0.012460975 lambda = 1; f = -1098.2779974 lambda = 1.9332; f = -1098.2828305 Norm of dx 0.0071459 ---- Improvement on iteration 65 = 0.022824888 ----------------- f at the beginning of new iteration, -1098.2828305000 Predicted improvement: 0.008159069 lambda = 1; f = -1098.2977433 lambda = 1.9332; f = -1098.3089287 lambda = 3.7372; f = -1098.3228180 Norm of dx 0.0014784 ---- Improvement on iteration 66 = 0.039987528 ----------------- f at the beginning of new iteration, -1098.3228180280 Predicted improvement: 0.013692234 lambda = 1; f = -1098.3430351 lambda = 1.9332; f = -1098.3483557 Norm of dx 0.0069179 ---- Improvement on iteration 67 = 0.025537644 ----------------- f at the beginning of new iteration, -1098.3483556723 Predicted improvement: 0.010770573 lambda = 1; f = -1098.3664562 lambda = 1.9332; f = -1098.3772846 Norm of dx 0.0047119 ---- Improvement on iteration 68 = 0.028928932 ----------------- f at the beginning of new iteration, -1098.3772846048 Predicted improvement: 0.020014545 lambda = 1; f = -1098.4074683 lambda = 1.9332; f = -1098.4180900 Norm of dx 0.012027 ---- Improvement on iteration 69 = 0.040805352 ----------------- f at the beginning of new iteration, -1098.4180899566 Predicted improvement: 0.012980220 lambda = 1; f = -1098.4392762 lambda = 1.9332; f = -1098.4505234 Norm of dx 0.0055747 ---- Improvement on iteration 70 = 0.032433393 ----------------- f at the beginning of new iteration, -1098.4505233501 Predicted improvement: 0.006472045 lambda = 1; f = -1098.4582005 Norm of dx 0.0048872 ---- Improvement on iteration 71 = 0.007677193 ----------------- f at the beginning of new iteration, -1098.4582005435 Predicted improvement: 0.001518914 lambda = 1; f = -1098.4604357 lambda = 1.9332; f = -1098.4611064 Norm of dx 0.0016064 ---- Improvement on iteration 72 = 0.002905877 ----------------- f at the beginning of new iteration, -1098.4611064201 Predicted improvement: 0.001304924 lambda = 1; f = -1098.4633504 lambda = 1.9332; f = -1098.4647717 lambda = 3.7372; f = -1098.4656686 Norm of dx 0.0019648 ---- Improvement on iteration 73 = 0.004562211 ----------------- f at the beginning of new iteration, -1098.4656686310 Predicted improvement: 0.002814289 lambda = 1; f = -1098.4704542 lambda = 1.9332; f = -1098.4733817 lambda = 3.7372; f = -1098.4748689 Norm of dx 0.0019464 ---- Improvement on iteration 74 = 0.009200306 ----------------- f at the beginning of new iteration, -1098.4748689372 Predicted improvement: 0.004391838 lambda = 1; f = -1098.4818643 lambda = 1.9332; f = -1098.4852364 Norm of dx 0.0040863 ---- Improvement on iteration 75 = 0.010367447 ----------------- f at the beginning of new iteration, -1098.4852363843 Predicted improvement: 0.001773104 lambda = 1; f = -1098.4873454 Norm of dx 0.0044892 ---- Improvement on iteration 76 = 0.002108990 ----------------- f at the beginning of new iteration, -1098.4873453740 Predicted improvement: 0.000595439 lambda = 1; f = -1098.4882675 lambda = 1.9332; f = -1098.4886730 Norm of dx 0.0015398 ---- Improvement on iteration 77 = 0.001327625 ----------------- f at the beginning of new iteration, -1098.4886729989 Predicted improvement: 0.000900901 lambda = 1; f = -1098.4903322 lambda = 1.9332; f = -1098.4916390 lambda = 3.7372; f = -1098.4935004 lambda = 7.2247; f = -1098.4945902 Norm of dx 0.0015041 ---- Improvement on iteration 78 = 0.005917203 ----------------- f at the beginning of new iteration, -1098.4945902019 Predicted improvement: 0.004519776 lambda = 1; f = -1098.5026701 lambda = 1.9332; f = -1098.5084033 lambda = 3.7372; f = -1098.5145973 Norm of dx 0.0034441 ---- Improvement on iteration 79 = 0.020007115 ----------------- f at the beginning of new iteration, -1098.5145973167 Predicted improvement: 0.004134189 lambda = 1; f = -1098.5196761 Norm of dx 0.010584 ---- Improvement on iteration 80 = 0.005078751 ----------------- f at the beginning of new iteration, -1098.5196760681 Predicted improvement: 0.000705492 lambda = 1; f = -1098.5206675 lambda = 1.9332; f = -1098.5208610 Norm of dx 0.0041211 ---- Improvement on iteration 81 = 0.001184885 ----------------- f at the beginning of new iteration, -1098.5208609533 Predicted improvement: 0.000482361 lambda = 1; f = -1098.5218005 lambda = 1.9332; f = -1098.5226229 lambda = 3.7372; f = -1098.5240638 lambda = 7.2247; f = -1098.5262941 lambda = 13.967; f = -1098.5285364 Norm of dx 0.0006816 ---- Improvement on iteration 82 = 0.007675464 ----------------- f at the beginning of new iteration, -1098.5285364169 Predicted improvement: 0.005482663 lambda = 1; f = -1098.5382581 lambda = 1.9332; f = -1098.5450595 lambda = 3.7372; f = -1098.5519942 Norm of dx 0.010132 ---- Improvement on iteration 83 = 0.023457770 ----------------- f at the beginning of new iteration, -1098.5519941864 Correct for low angle: 0.00154733 Predicted improvement: 0.009926632 lambda = 1; f = -1098.4912212 lambda = 0.33333; f = -1098.5495727 lambda = 0.11111; f = -1098.5532404 Norm of dx 0.013076 ---- Improvement on iteration 84 = 0.001246243 ----------------- f at the beginning of new iteration, -1098.5532404298 Correct for low angle: 0.00368749 Predicted improvement: 0.003213527 lambda = 1; f = -1098.5486956 lambda = 0.33333; f = -1098.5541329 Norm of dx 0.012243 ---- Improvement on iteration 85 = 0.000892498 ----------------- f at the beginning of new iteration, -1098.5541329274 Correct for low angle: 0.00135296 Predicted improvement: 0.006405727 lambda = 1; f = -1098.5188806 lambda = 0.33333; f = -1098.5530695 lambda = 0.11111; f = -1098.5549937 Norm of dx 0.0089471 ---- Improvement on iteration 86 = 0.000860797 ----------------- f at the beginning of new iteration, -1098.5549937239 Predicted improvement: 0.001101184 lambda = 1; f = -1098.5562682 Norm of dx 0.0081435 ---- Improvement on iteration 87 = 0.001274434 ----------------- f at the beginning of new iteration, -1098.5562681580 Predicted improvement: 0.000188861 lambda = 1; f = -1098.5565866 lambda = 1.9332; f = -1098.5567980 lambda = 3.7372; f = -1098.5569715 Norm of dx 0.0013103 ---- Improvement on iteration 88 = 0.000703338 ----------------- f at the beginning of new iteration, -1098.5569714957 Predicted improvement: 0.000529061 lambda = 1; f = -1098.5580033 lambda = 1.9332; f = -1098.5589285 lambda = 3.7372; f = -1098.5606136 lambda = 7.2247; f = -1098.5634846 lambda = 13.967; f = -1098.5675871 lambda = 27; f = -1098.5700868 Norm of dx 0.0009292 ---- Improvement on iteration 89 = 0.013115343 ----------------- f at the beginning of new iteration, -1098.5700868387 Predicted improvement: 0.004094008 lambda = 1; f = -1098.5758759 lambda = 1.9332; f = -1098.5767916 Norm of dx 0.0055854 ---- Improvement on iteration 90 = 0.006704797 ----------------- f at the beginning of new iteration, -1098.5767916362 Predicted improvement: 0.000515462 lambda = 1; f = -1098.5774356 Norm of dx 0.0021967 ---- Improvement on iteration 91 = 0.000643933 ----------------- f at the beginning of new iteration, -1098.5774355690 Predicted improvement: 0.000233159 lambda = 1; f = -1098.5778256 lambda = 1.9332; f = -1098.5780693 lambda = 3.7372; f = -1098.5782105 Norm of dx 0.0013582 ---- Improvement on iteration 92 = 0.000774979 ----------------- f at the beginning of new iteration, -1098.5782105483 Predicted improvement: 0.000546528 lambda = 1; f = -1098.5792661 lambda = 1.9332; f = -1098.5801734 lambda = 3.7372; f = -1098.5817147 lambda = 7.2247; f = -1098.5838991 lambda = 13.967; f = -1098.5851487 Norm of dx 0.00093661 ---- Improvement on iteration 93 = 0.006938172 ----------------- f at the beginning of new iteration, -1098.5851487204 Predicted improvement: 0.000961443 lambda = 1; f = -1098.5863024 Norm of dx 0.0039147 ---- Improvement on iteration 94 = 0.001153698 ----------------- f at the beginning of new iteration, -1098.5863024183 Predicted improvement: 0.000244245 lambda = 1; f = -1098.5866800 lambda = 1.9332; f = -1098.5868547 Norm of dx 0.0017305 ---- Improvement on iteration 95 = 0.000552240 ----------------- f at the beginning of new iteration, -1098.5868546583 Predicted improvement: 0.000375586 lambda = 1; f = -1098.5875589 lambda = 1.9332; f = -1098.5881384 lambda = 3.7372; f = -1098.5890453 lambda = 7.2247; f = -1098.5899972 Norm of dx 0.001648 ---- Improvement on iteration 96 = 0.003142534 ----------------- f at the beginning of new iteration, -1098.5899971925 Predicted improvement: 0.002235328 lambda = 1; f = -1098.5938293 lambda = 1.9332; f = -1098.5962425 lambda = 3.7372; f = -1098.5977236 Norm of dx 0.0060409 ---- Improvement on iteration 97 = 0.007726414 ----------------- f at the beginning of new iteration, -1098.5977236060 Predicted improvement: 0.000724755 lambda = 1; f = -1098.5985542 Norm of dx 0.0050845 ---- Improvement on iteration 98 = 0.000830547 ----------------- f at the beginning of new iteration, -1098.5985541532 Predicted improvement: 0.000043081 lambda = 1; f = -1098.5986099 Norm of dx 0.00033229 ---- Improvement on iteration 99 = 0.000055741 ----------------- f at the beginning of new iteration, -1098.5986098941 Predicted improvement: 0.000038693 lambda = 1; f = -1098.5986691 lambda = 1.9332; f = -1098.5987004 Norm of dx 0.0001581 ---- Improvement on iteration 100 = 0.000090542 ----------------- f at the beginning of new iteration, -1098.5987004361 Predicted improvement: 0.000083495 lambda = 1; f = -1098.5988456 lambda = 1.9332; f = -1098.5989528 lambda = 3.7372; f = -1098.5990830 Norm of dx 0.0004708 ---- Improvement on iteration 101 = 0.000382578 ----------------- f at the beginning of new iteration, -1098.5990830144 Predicted improvement: 0.000332197 lambda = 1; f = -1098.5996444 lambda = 1.9332; f = -1098.5999991 lambda = 3.7372; f = -1098.6002223 Norm of dx 0.002061 ---- Improvement on iteration 102 = 0.001139296 ----------------- f at the beginning of new iteration, -1098.6002223106 Predicted improvement: 0.000306145 lambda = 1; f = -1098.6006608 lambda = 1.9332; f = -1098.6007178 Norm of dx 0.000359 ---- Improvement on iteration 103 = 0.000495477 ----------------- f at the beginning of new iteration, -1098.6007177873 Predicted improvement: 0.000033189 lambda = 1; f = -1098.6007492 Norm of dx 0.00028947 ---- Improvement on iteration 104 = 0.000031366 ----------------- f at the beginning of new iteration, -1098.6007491532 Predicted improvement: 0.000008632 lambda = 1; f = -1098.6007634 lambda = 1.9332; f = -1098.6007744 lambda = 3.7372; f = -1098.6007896 Norm of dx 0.00010437 ---- Improvement on iteration 105 = 0.000040494 ----------------- f at the beginning of new iteration, -1098.6007896474 Predicted improvement: 0.000063502 lambda = 1; f = -1098.6008968 lambda = 1.9332; f = -1098.6009716 lambda = 3.7372; f = -1098.6010477 Norm of dx 0.0006783 ---- Improvement on iteration 106 = 0.000258021 ----------------- f at the beginning of new iteration, -1098.6010476681 Predicted improvement: 0.000216031 lambda = 1; f = -1098.6014504 lambda = 1.9332; f = -1098.6017794 lambda = 3.7372; f = -1098.6022870 lambda = 7.2247; f = -1098.6027896 Norm of dx 0.0019899 ---- Improvement on iteration 107 = 0.001741943 ----------------- f at the beginning of new iteration, -1098.6027896109 Predicted improvement: 0.000578247 lambda = 1; f = -1098.6035917 Norm of dx 0.0038202 ---- Improvement on iteration 108 = 0.000802044 ----------------- f at the beginning of new iteration, -1098.6035916548 Predicted improvement: 0.000138031 lambda = 1; f = -1098.6037646 Norm of dx 0.0013135 ---- Improvement on iteration 109 = 0.000172919 ----------------- f at the beginning of new iteration, -1098.6037645743 Predicted improvement: 0.000031329 lambda = 1; f = -1098.6038262 lambda = 1.9332; f = -1098.6038763 lambda = 3.7372; f = -1098.6039532 lambda = 7.2247; f = -1098.6040268 Norm of dx 0.00042411 ---- Improvement on iteration 110 = 0.000262265 ----------------- f at the beginning of new iteration, -1098.6040268392 Predicted improvement: 0.000207382 lambda = 1; f = -1098.6044364 lambda = 1.9332; f = -1098.6048050 lambda = 3.7372; f = -1098.6054800 lambda = 7.2247; f = -1098.6066447 lambda = 13.967; f = -1098.6083706 lambda = 27; f = -1098.6097301 Norm of dx 0.0018052 ---- Improvement on iteration 111 = 0.005703212 ----------------- f at the beginning of new iteration, -1098.6097300509 Predicted improvement: 0.000780403 lambda = 1; f = -1098.6106306 Norm of dx 0.0022923 ---- Improvement on iteration 112 = 0.000900503 ----------------- f at the beginning of new iteration, -1098.6106305539 Predicted improvement: 0.000102838 lambda = 1; f = -1098.6107800 lambda = 1.9332; f = -1098.6108380 Norm of dx 0.0010411 ---- Improvement on iteration 113 = 0.000207492 ----------------- f at the beginning of new iteration, -1098.6108380459 Predicted improvement: 0.000129860 lambda = 1; f = -1098.6110841 lambda = 1.9332; f = -1098.6112915 lambda = 3.7372; f = -1098.6116317 lambda = 7.2247; f = -1098.6120628 Norm of dx 0.0013619 ---- Improvement on iteration 114 = 0.001224706 ----------------- f at the beginning of new iteration, -1098.6120627518 Correct for low angle: 0.00430341 Predicted improvement: 0.000781693 lambda = 1; f = -1098.6129817 Norm of dx 0.0071592 ---- Improvement on iteration 115 = 0.000918996 ----------------- f at the beginning of new iteration, -1098.6129817482 Correct for low angle: 0.0017347 Predicted improvement: 0.000852346 lambda = 1; f = -1098.6115046 lambda = 0.33333; f = -1098.6131047 lambda = 0.11111; f = -1098.6130903 Norm of dx 0.0023295 ---- Improvement on iteration 116 = 0.000122924 ----------------- f at the beginning of new iteration, -1098.6131046721 Correct for low angle: 0.00346656 Predicted improvement: 0.000126876 lambda = 1; f = -1098.6131816 Norm of dx 0.0015937 ---- Improvement on iteration 117 = 0.000076884 ----------------- f at the beginning of new iteration, -1098.6131815563 Predicted improvement: 0.000143573 lambda = 1; f = -1098.6132687 Norm of dx 0.00020418 ---- Improvement on iteration 118 = 0.000087161 ----------------- f at the beginning of new iteration, -1098.6132687174 Predicted improvement: 0.000029498 lambda = 1; f = -1098.6133081 Norm of dx 0.00021242 ---- Improvement on iteration 119 = 0.000039388 ----------------- f at the beginning of new iteration, -1098.6133081059 Predicted improvement: 0.000261290 lambda = 1; f = -1098.6136284 Norm of dx 0.0022438 ---- Improvement on iteration 120 = 0.000320315 ----------------- f at the beginning of new iteration, -1098.6136284204 Correct for low angle: 0.00150608 Predicted improvement: 0.001078850 lambda = 1; f = -1098.6117598 lambda = 0.33333; f = -1098.6139951 Norm of dx 0.0039014 ---- Improvement on iteration 121 = 0.000366688 ----------------- f at the beginning of new iteration, -1098.6139951084 Correct for low angle: 0.00164517 Predicted improvement: 0.002002402 lambda = 1; f = -1098.6012195 lambda = 0.33333; f = -1098.6133643 lambda = 0.11111; f = -1098.6141769 Norm of dx 0.0062376 ---- Improvement on iteration 122 = 0.000181759 ----------------- f at the beginning of new iteration, -1098.6141768671 Correct for low angle: 0.00492902 Predicted improvement: 0.000568842 lambda = 1; f = -1098.6149651 Norm of dx 0.00664 ---- Improvement on iteration 123 = 0.000788235 ----------------- f at the beginning of new iteration, -1098.6149651022 Correct for low angle: 0.00259438 Predicted improvement: 0.000417533 lambda = 1; f = -1098.6099779 lambda = 0.33333; f = -1098.6146846 lambda = 0.11111; f = -1098.6150280 Norm of dx 0.0054313 ---- Improvement on iteration 124 = 0.000062938 ----------------- f at the beginning of new iteration, -1098.6150280398 Correct for low angle: 0.00114715 Predicted improvement: 0.000898650 lambda = 1; f = -1098.6015200 lambda = 0.33333; f = -1098.6138417 lambda = 0.11111; f = -1098.6149917 lambda = 0.037037; f = -1098.6150555 Norm of dx 0.0048735 ---- Improvement on iteration 125 = 0.000027443 ----------------- f at the beginning of new iteration, -1098.6150554831 Correct for low angle: 0.00322524 Predicted improvement: 0.000251367 lambda = 1; f = -1098.6125334 lambda = 0.33333; f = -1098.6148236 lambda = 0.11111; f = -1098.6150450 lambda = 0.037037; f = -1098.6150594 lambda = 0.012346; f = -1098.6150576 Norm of dx 0.0047147 ---- Improvement on iteration 126 = 0.000003912 ----------------- f at the beginning of new iteration, -1098.6150593955 Predicted improvement: 0.000148241 lambda = 1; f = -1098.6152160 Norm of dx 0.0045528 ---- Improvement on iteration 127 = 0.000156650 ----------------- f at the beginning of new iteration, -1098.6152160458 Predicted improvement: 0.000009181 lambda = 1; f = -1098.6152340 lambda = 1.9332; f = -1098.6152496 lambda = 3.7372; f = -1098.6152766 lambda = 7.2247; f = -1098.6153170 lambda = 13.967; f = -1098.6153509 Norm of dx 0.00033748 ---- Improvement on iteration 128 = 0.000134857 ----------------- f at the beginning of new iteration, -1098.6153509031 Predicted improvement: 0.000113674 lambda = 1; f = -1098.6155706 lambda = 1.9332; f = -1098.6157621 lambda = 3.7372; f = -1098.6160950 lambda = 7.2247; f = -1098.6165994 lambda = 13.967; f = -1098.6170536 Norm of dx 0.0010036 ---- Improvement on iteration 129 = 0.001702744 ----------------- f at the beginning of new iteration, -1098.6170536467 Predicted improvement: 0.000052093 lambda = 1; f = -1098.6171063 Norm of dx 0.00093159 ---- Improvement on iteration 130 = 0.000052703 ----------------- f at the beginning of new iteration, -1098.6171063493 Predicted improvement: 0.000003917 lambda = 1; f = -1098.6171119 lambda = 1.9332; f = -1098.6171151 Norm of dx 0.00015508 ---- Improvement on iteration 131 = 0.000008716 ----------------- f at the beginning of new iteration, -1098.6171150655 Predicted improvement: 0.000012433 lambda = 1; f = -1098.6171345 lambda = 1.9332; f = -1098.6171467 Norm of dx 0.00033951 ---- Improvement on iteration 132 = 0.000031680 ----------------- f at the beginning of new iteration, -1098.6171467458 Predicted improvement: 0.000042375 lambda = 1; f = -1098.6172126 lambda = 1.9332; f = -1098.6172474 Norm of dx 0.00091315 ---- Improvement on iteration 133 = 0.000100638 ----------------- f at the beginning of new iteration, -1098.6172473838 Predicted improvement: 0.000067169 lambda = 1; f = -1098.6173503 lambda = 1.9332; f = -1098.6173927 Norm of dx 0.0012295 ---- Improvement on iteration 134 = 0.000145280 ----------------- f at the beginning of new iteration, -1098.6173926636 Predicted improvement: 0.000028164 lambda = 1; f = -1098.6174324 lambda = 1.9332; f = -1098.6174321 Norm of dx 0.00056457 ---- Improvement on iteration 135 = 0.000039746 ----------------- f at the beginning of new iteration, -1098.6174324095 Predicted improvement: 0.000003139 lambda = 1; f = -1098.6174375 lambda = 1.9332; f = -1098.6174367 Norm of dx 0.00027725 ---- Improvement on iteration 136 = 0.000005136 ----------------- f at the beginning of new iteration, -1098.6174375452 Predicted improvement: 0.000000021 lambda = 1; f = -1098.6174376 lambda = 1.9332; f = -1098.6174377 lambda = 3.7372; f = -1098.6174378 lambda = 7.2247; f = -1098.6174380 lambda = 13.967; f = -1098.6174383 lambda = 27; f = -1098.6174385 lambda = 52.196; f = -1098.6174375 lambda = 35.146; f = -1098.6174384 Norm of dx 8.3422e-06 ---- Improvement on iteration 137 = 0.000000970 ----------------- f at the beginning of new iteration, -1098.6174385156 Predicted improvement: 0.000000481 lambda = 1; f = -1098.6174386 lambda = 0.33333; f = -1098.6174386 Norm of dx 0.00012214 ---- Improvement on iteration 138 = 0.000000113 ----------------- f at the beginning of new iteration, -1098.6174386284 Predicted improvement: 0.000000400 lambda = 1; f = -1098.6174388 lambda = 0.33333; f = -1098.6174387 Norm of dx 9.7554e-05 ---- Improvement on iteration 139 = 0.000000132 ----------------- f at the beginning of new iteration, -1098.6174387601 Predicted improvement: 0.000000436 lambda = 1; f = -1098.6174389 lambda = 0.33333; f = -1098.6174389 Norm of dx 9.6611e-05 ---- Improvement on iteration 140 = 0.000000173 ----------------- f at the beginning of new iteration, -1098.6174389333 Predicted improvement: 0.000000113 lambda = 1; f = -1098.6174391 Norm of dx 4.422e-05 ---- Improvement on iteration 141 = 0.000000155 ----------------- f at the beginning of new iteration, -1098.6174390886 Predicted improvement: 0.000000012 lambda = 1; f = -1098.6174392 lambda = 1.9332; f = -1098.6174393 lambda = 3.7372; f = -1098.6174393 lambda = 7.2247; f = -1098.6174393 lambda = 13.967; f = -1098.6174384 lambda = 9.4043; f = -1098.6174391 lambda = 6.3323; f = -1098.6174393 lambda = 8.0283; f = -1098.6174392 lambda = 10.178; f = -1098.6174390 lambda = 8.8277; f = -1098.6174392 Norm of dx 2.1107e-05 ---- Improvement on iteration 142 = 0.000000241 warning: possible inaccuracy in H matrix ----------------- f at the beginning of new iteration, -1098.6174393300 Predicted improvement: 0.000000075 lambda = 1; f = -1098.6174392 lambda = 0.33333; f = -1098.6174393 lambda = 0.11111; f = -1098.6174393 lambda = 0.037037; f = -1098.6174393 lambda = 0.012346; f = -1098.6174393 lambda = 0.0041152; f = -1098.6174393 lambda = 0.0013717; f = -1098.6174393 lambda = 0.00045725; f = -1098.6174393 lambda = 0.00015242; f = -1098.6174393 lambda = 5.0805e-05; f = -1098.6174393 lambda = 1.6935e-05; f = -1098.6174393 lambda = 5.645e-06; f = -1098.6174393 lambda = 1.8817e-06; f = -1098.6174393 lambda = 6.2723e-07; f = -1098.6174393 lambda = 2.0908e-07; f = -1098.6174393 lambda = 6.9692e-08; f = -1098.6174393 lambda = 2.3231e-08; f = -1098.6174393 lambda = 7.7435e-09; f = -1098.6174393 lambda = 1.497e-08; f = -1098.6174393 lambda = 2.8939e-08; f = -1098.6174393 lambda = 1.9486e-08; f = -1098.6174393 lambda = 1.3121e-08; f = -1098.6174393 lambda = 1.6635e-08; f = -1098.6174393 lambda = 1.4427e-08; f = -1098.6174393 lambda = 1.3246e-08; f = -1098.6174393 Norm of dx 5.4281e-05 Cliff. Perturbing search direction. Predicted improvement: 0.000000112 lambda = 1; f = -1098.6174391 lambda = 0.33333; f = -1098.6174393 lambda = 0.11111; f = -1098.6174393 lambda = 0.037037; f = -1098.6174393 lambda = 0.012346; f = -1098.6174393 lambda = 0.0041152; f = -1098.6174393 lambda = 0.0013717; f = -1098.6174393 lambda = 0.00045725; f = -1098.6174393 lambda = 0.00015242; f = -1098.6174393 lambda = 5.0805e-05; f = -1098.6174393 lambda = 1.6935e-05; f = -1098.6174393 lambda = 5.645e-06; f = -1098.6174393 lambda = 1.8817e-06; f = -1098.6174393 lambda = 6.2723e-07; f = -1098.6174393 lambda = 1.2125e-06; f = -1098.6174393 lambda = 8.1646e-07; f = -1098.6174393 lambda = 6.4398e-07; f = -1098.6174393 lambda = 6.3221e-07; f = -1098.6174393 Norm of dx 7.0747e-05 Cliff again. Try traversing Predicted improvement: 0.000013546 lambda = 1; f = -1098.6164634 lambda = 0.33333; f = -1098.6173313 lambda = 0.11111; f = -1098.6174274 lambda = 0.037037; f = -1098.6174380 lambda = 0.012346; f = -1098.6174392 lambda = 0.0041152; f = -1098.6174393 lambda = 0.0013717; f = -1098.6174393 lambda = 0.00045725; f = -1098.6174393 lambda = 0.00015242; f = -1098.6174393 lambda = 5.0805e-05; f = -1098.6174393 lambda = 1.6935e-05; f = -1098.6174393 lambda = 5.645e-06; f = -1098.6174393 lambda = 1.8817e-06; f = -1098.6174393 lambda = 6.2723e-07; f = -1098.6174393 lambda = 2.0908e-07; f = -1098.6174393 lambda = 6.9692e-08; f = -1098.6174393 lambda = 2.3231e-08; f = -1098.6174393 lambda = 7.7435e-09; f = -1098.6174393 lambda = 1.497e-08; f = -1098.6174393 lambda = 1.008e-08; f = -1098.6174393 lambda = 1.2779e-08; f = -1098.6174393 lambda = 1.1083e-08; f = -1098.6174393 lambda = 1.0176e-08; f = -1098.6174393 lambda = 1.0711e-08; f = -1098.6174393 lambda = 1.1274e-08; f = -1098.6174393 lambda = 1.0933e-08; f = -1098.6174393 lambda = 1.0602e-08; f = -1098.6174393 lambda = 1.0799e-08; f = -1098.6174393 lambda = 1.068e-08; f = -1098.6174393 lambda = 1.0563e-08; f = -1098.6174393 lambda = 1.0446e-08; f = -1098.6174393 lambda = 1.0331e-08; f = -1098.6174393 lambda = 1.0218e-08; f = -1098.6174393 lambda = 1.0105e-08; f = -1098.6174393 Norm of dx 0.005205 ---- Improvement on iteration 143 = 0.000000000 improvement < crit termination back and forth on step length never finished Final value of minus the log posterior (or likelihood):-1098.617439 MODE CHECK Fval obtained by the minimization routine (minus the posterior/likelihood)): -1098.617439 RESULTS FROM POSTERIOR ESTIMATION parameters prior mean mode s.d. prior pstdev eta 1.500 1.1917 0.1844 gamm 0.2500 chi 0.020 0.0199 0.0010 norm 0.0010 phi 0.200 0.2022 0.0101 beta 0.0100 sigma 1.500 1.2349 0.3241 gamm 0.3700 vartheta 2.000 1.8047 0.7014 gamm 0.7500 zeta 0.700 0.5151 0.1113 beta 0.1000 rho 0.750 0.7585 0.0473 beta 0.1000 varrho_d 0.400 0.3395 0.0771 gamm 0.1000 varrho_y 0.250 0.1537 0.0897 gamm 0.1500 varrho_pi 1.500 1.6287 0.1918 gamm 0.2000 rho_c 0.800 0.8155 0.0959 beta 0.1000 rho_d 0.800 0.8934 0.0612 beta 0.1000 rho_f 0.800 0.8217 0.1122 beta 0.1000 rho_h 0.800 0.8461 0.1001 beta 0.1000 rho_i 0.800 0.6363 0.1063 beta 0.1000 rho_w 0.800 0.8301 0.0861 beta 0.1000 rho_z 0.800 0.8462 0.1002 beta 0.1000 rho1_i_star 0.800 0.8535 0.0769 beta 0.1000 rho1_pi_star 0.800 0.8233 0.1019 beta 0.1000 rho1_y_star 0.800 0.8655 0.0909 beta 0.1000 theta_f 0.700 0.8163 0.0422 beta 0.0900 theta_h 0.700 0.7567 0.0909 beta 0.0900 theta_w 0.700 0.7765 0.0609 beta 0.0900 varphi_f 0.700 0.7113 0.0497 beta 0.0500 varphi_h 0.700 0.7092 0.0497 beta 0.0500 varphi_w 0.700 0.7089 0.0503 beta 0.0500 standard deviation of shocks prior mean mode s.d. prior pstdev eps_c 0.005 0.0099 0.0036 invg Inf eps_d 0.005 0.0081 0.0017 invg Inf eps_f 0.005 0.0061 0.0011 invg Inf eps_h 0.005 0.0023 0.0009 invg Inf eps_i 0.005 0.0034 0.0010 invg Inf eps_w 0.005 0.0021 0.0007 invg Inf eps_z 0.005 0.0023 0.0009 invg Inf eps_i_star 0.005 0.0010 0.0001 invg Inf eps_pi_star 0.005 0.0022 0.0008 invg Inf eps_y_star 0.005 0.0023 0.0010 invg Inf standard deviation of measurement errors prior mean mode s.d. prior pstdev y_obs 0.002 0.0009 0.0004 invg Inf pi_obs 0.002 0.0009 0.0003 invg Inf d_obs 0.002 0.0009 0.0003 invg Inf i_obs 0.002 0.0024 0.0006 invg Inf y_star_obs 0.005 0.0057 0.0008 invg Inf pi_star_obs 0.005 0.0068 0.0009 invg Inf i_star_obs 0.005 0.0009 0.0001 invg Inf Log data density [Laplace approximation] is 941.473988. Estimation::mcmc: Multiple chains mode. Estimation::mcmc: Old mh-files successfully erased! Estimation::mcmc: Old metropolis.log file successfully erased! Estimation::mcmc: Creation of a new metropolis.log file. Estimation::mcmc: Searching for initial values... Estimation::mcmc: Initial values found! Estimation::mcmc: Write details about the MCMC... Ok! Estimation::mcmc: Details about the MCMC are available in GH_SOE_est_full_Analysis/metropolis\GH_SOE_est_full_Analysis_mh_history_0.mat Estimation::mcmc: Number of mh files: 1 per block. Estimation::mcmc: Total number of generated files: 2. Estimation::mcmc: Total number of iterations: 100000. Estimation::mcmc: Current acceptance ratio per chain: Chain 1: 30.887% Chain 2: 30.675% Estimation::mcmc: Total number of MH draws per chain: 100000. Estimation::mcmc: Total number of generated MH files: 1. Estimation::mcmc: I'll use mh-files 1 to 1. Estimation::mcmc: In MH-file number 1 I'll start at line 45001. Estimation::mcmc: Finally I keep 55000 draws per chain. MCMC Inefficiency factors per block Parameter Block 1 Block 2 SE_eps_c 216.504 183.817 SE_eps_d 191.690 160.711 SE_eps_f 339.574 280.570 SE_eps_h 597.343 552.791 SE_eps_i 258.072 322.768 SE_eps_w 479.200 403.645 SE_eps_z 529.773 485.964 SE_eps_i_star 183.801 183.538 SE_eps_pi_star 284.136 334.901 SE_eps_y_star 384.235 379.828 SE_EOBS_y_obs 381.827 565.101 SE_EOBS_pi_obs 505.599 489.507 SE_EOBS_d_obs 724.770 553.980 SE_EOBS_i_obs 238.724 214.933 SE_EOBS_y_star_obs 403.035 401.908 SE_EOBS_pi_star_obs 291.313 308.820 SE_EOBS_i_star_obs 232.312 182.006 eta 156.261 135.725 chi 114.815 110.992 phi 98.141 169.017 sigma 173.068 137.546 vartheta 214.653 163.632 zeta 124.866 132.823 rho 221.543 194.768 varrho_d 205.158 182.683 varrho_y 159.085 151.916 varrho_pi 179.822 166.761 rho_c 214.333 157.284 rho_d 135.707 120.084 rho_f 127.505 120.271 rho_h 166.339 164.122 rho_i 131.467 129.502 rho_w 206.156 201.781 rho_z 143.050 166.626 rho1_i_star 190.185 151.572 rho1_pi_star 139.679 141.083 rho1_y_star 171.479 187.032 theta_f 181.745 139.118 theta_h 207.330 209.136 theta_w 119.097 133.108 varphi_f 162.733 146.343 varphi_h 148.719 141.836 varphi_w 142.388 128.013 Estimation::mcmc::diagnostics: Univariate convergence diagnostic, Brooks and Gelman (1998): Parameter 1... Done! Parameter 2... Done! Parameter 3... Done! Parameter 4... Done! Parameter 5... Done! Parameter 6... Done! Parameter 7... Done! Parameter 8... Done! Parameter 9... Done! Parameter 10... Done! Parameter 11... Done! Parameter 12... Done! Parameter 13... Done! Parameter 14... Done! Parameter 15... Done! Parameter 16... Done! Parameter 17... Done! Parameter 18... Done! Parameter 19... Done! Parameter 20... Done! Parameter 21... Done! Parameter 22... Done! Parameter 23... Done! Parameter 24... Done! Parameter 25... Done! Parameter 26... Done! Parameter 27... Done! Parameter 28... Done! Parameter 29... Done! Parameter 30... Done! Parameter 31... Done! Parameter 32... Done! Parameter 33... Done! Parameter 34... Done! Parameter 35... Done! Parameter 36... Done! Parameter 37... Done! Parameter 38... Done! Parameter 39... Done! Parameter 40... Done! Parameter 41... Done! Parameter 42... Done! Parameter 43... Done! Estimation::marginal density: I'm computing the posterior mean and covariance... Done! Estimation::marginal density: I'm computing the posterior log marginal density (modified harmonic mean)... Done! ESTIMATION RESULTS Log data density is 943.790127. parameters prior mean post. mean 90% HPD interval prior pstdev eta 1.500 1.2001 0.9046 1.4885 gamm 0.2500 chi 0.020 0.0199 0.0183 0.0215 norm 0.0010 phi 0.200 0.2028 0.1864 0.2191 beta 0.0100 sigma 1.500 1.2966 0.7660 1.8205 gamm 0.3700 vartheta 2.000 2.1334 0.9090 3.2579 gamm 0.7500 zeta 0.700 0.5562 0.3858 0.7338 beta 0.1000 rho 0.750 0.7520 0.6687 0.8370 beta 0.1000 varrho_d 0.400 0.3779 0.2328 0.5149 gamm 0.1000 varrho_y 0.250 0.1854 0.0407 0.3201 gamm 0.1500 varrho_pi 1.500 1.6640 1.3436 1.9817 gamm 0.2000 rho_c 0.800 0.7341 0.5748 0.9094 beta 0.1000 rho_d 0.800 0.8679 0.7781 0.9651 beta 0.1000 rho_f 0.800 0.7985 0.6515 0.9540 beta 0.1000 rho_h 0.800 0.8003 0.6517 0.9550 beta 0.1000 rho_i 0.800 0.6032 0.4319 0.7681 beta 0.1000 rho_w 0.800 0.7787 0.6394 0.9319 beta 0.1000 rho_z 0.800 0.7986 0.6449 0.9643 beta 0.1000 rho1_i_star 0.800 0.8178 0.6920 0.9487 beta 0.1000 rho1_pi_star 0.800 0.7779 0.6280 0.9393 beta 0.1000 rho1_y_star 0.800 0.8491 0.7207 0.9762 beta 0.1000 theta_f 0.700 0.8062 0.7318 0.8804 beta 0.0900 theta_h 0.700 0.7201 0.5711 0.8766 beta 0.0900 theta_w 0.700 0.7695 0.6740 0.8621 beta 0.0900 varphi_f 0.700 0.7096 0.6289 0.7944 beta 0.0500 varphi_h 0.700 0.7075 0.6272 0.7887 beta 0.0500 varphi_w 0.700 0.7022 0.6228 0.7841 beta 0.0500 standard deviation of shocks prior mean post. mean 90% HPD interval prior pstdev eps_c 0.005 0.0132 0.0067 0.0195 invg Inf eps_d 0.005 0.0090 0.0060 0.0121 invg Inf eps_f 0.005 0.0054 0.0028 0.0079 invg Inf eps_h 0.005 0.0045 0.0012 0.0089 invg Inf eps_i 0.005 0.0043 0.0023 0.0062 invg Inf eps_w 0.005 0.0032 0.0013 0.0052 invg Inf eps_z 0.005 0.0043 0.0012 0.0079 invg Inf eps_i_star 0.005 0.0010 0.0008 0.0013 invg Inf eps_pi_star 0.005 0.0033 0.0013 0.0054 invg Inf eps_y_star 0.005 0.0036 0.0014 0.0060 invg Inf standard deviation of measurement errors prior mean post. mean 90% HPD interval prior pstdev y_obs 0.002 0.0015 0.0005 0.0026 invg Inf pi_obs 0.002 0.0016 0.0005 0.0027 invg Inf d_obs 0.002 0.0029 0.0004 0.0075 invg Inf i_obs 0.002 0.0023 0.0009 0.0034 invg Inf y_star_obs 0.005 0.0049 0.0023 0.0070 invg Inf pi_star_obs 0.005 0.0063 0.0042 0.0086 invg Inf i_star_obs 0.005 0.0009 0.0007 0.0012 invg Inf Total computing time : 0h13m58s