Starting preprocessing of the model file ... Found 8 equation(s). Evaluating expressions...done Computing static model derivatives (order 1). Computing dynamic model derivatives (order 2). Processing outputs ... done Preprocessing completed. STEADY-STATE RESULTS: i 0 y 0 p 0 z 0 g 0 y_obs 0 pi_obs 0 ir_obs 0 EIGENVALUES: Modulus Real Imaginary 0.06251 0.06251 0 0.1609 0.1609 0 0.3966 0.3966 0 0.9 0.9 0 0.95 0.95 0 1.837 1.699 0.6983 1.837 1.699 -0.6983 2.449e+17 -2.449e+17 0 There are 3 eigenvalue(s) larger than 1 in modulus for 3 forward-looking variable(s) The rank condition is verified. Informations about jp_nk_rkdata (dynamic model) There is no block decomposition of the model. Use 'block' model's option. MODEL_DIAGNOSTICS: No obvious problems with this mod-file were detected. Initial value of the log posterior (or likelihood): -5877.7304 ----------------- f at the beginning of new iteration, 5877.7303544283 Predicted improvement: 46597.916439964 lambda = 1; f = 5880.5662467 lambda = 0.33333; f = 5877.8860511 lambda = 0.11111; f = 5877.7314005 lambda = 0.037037; f = 2948.4393359 lambda = 0.071599; f = 1189.9103880 lambda = 0.13841; f = 5877.7306721 lambda = 0.0932; f = 633.7725779 Norm of dx 3.0528 ---- Improvement on iteration 1 = 5243.957776566 ----------------- f at the beginning of new iteration, 633.7725778622 Predicted improvement: 359.192272296 lambda = 1; f = 633.7780911 lambda = 0.33333; f = 492.8091403 Norm of dx 0.2296 ---- Improvement on iteration 2 = 140.963437533 ----------------- f at the beginning of new iteration, 492.8091403296 Predicted improvement: 85.217202603 lambda = 1; f = 492.8125154 lambda = 0.33333; f = 492.8094655 lambda = 0.11111; f = 492.8091622 lambda = 0.037037; f = 492.8091404 lambda = 0.012346; f = 490.8755165 lambda = 0.023866; f = 489.4729744 lambda = 0.046138; f = 492.8091409 lambda = 0.031067; f = 488.9109505 lambda = 0.039387; f = 492.8091405 lambda = 0.03416; f = 492.8091403 lambda = 0.031363; f = 488.8954848 lambda = 0.033013; f = 488.8236146 lambda = 0.034749; f = 492.8091403 lambda = 0.033696; f = 492.8091403 lambda = 0.03308; f = 488.8212134 lambda = 0.033449; f = 492.8091403 Norm of dx 0.14168 Cliff. Perturbing search direction. Predicted improvement: 130.605208875 lambda = 1; f = 492.8221132 lambda = 0.33333; f = 492.8104823 lambda = 0.11111; f = 492.8092587 lambda = 0.037037; f = 492.8091456 lambda = 0.012346; f = 490.2256322 lambda = 0.023866; f = 492.8091409 lambda = 0.01607; f = 489.8541348 lambda = 0.020374; f = 492.8091405 lambda = 0.01767; f = 492.8091403 lambda = 0.016224; f = 489.8461120 Norm of dx 0.2006 badg2 = 0 ---- Improvement on iteration 3 = 3.987926961 back and forth on step length never finished ----------------- f at the beginning of new iteration, 488.8212133689 Predicted improvement: 85.217202603 lambda = 1; f = 488.8248234 lambda = 0.33333; f = 488.8216142 lambda = 0.11111; f = 488.8212578 lambda = 0.037037; f = 488.8212183 lambda = 0.012346; f = 488.8212139 lambda = 0.0041152; f = 488.8212134 lambda = 0.0013717; f = 488.8212134 lambda = 0.00045725; f = 488.8212134 lambda = 0.00015242; f = 488.8159810 Norm of dx 0.14168 ---- Improvement on iteration 4 = 0.005232350 ----------------- f at the beginning of new iteration, 488.8159810188 Predicted improvement: 84.375586278 lambda = 1; f = 488.8159844 lambda = 0.33333; f = 511.4127861 lambda = 0.11111; f = 488.3930133 lambda = 0.037037; f = 486.3010202 Norm of dx 0.12853 ---- Improvement on iteration 5 = 2.514960789 ----------------- f at the beginning of new iteration, 486.3010202295 Predicted improvement: 99.772733030 lambda = 1; f = 486.3010203 lambda = 0.33333; f = 446.2448019 Norm of dx 0.22827 ---- Improvement on iteration 6 = 40.056218304 ----------------- f at the beginning of new iteration, 446.2448019255 Predicted improvement: 10.051679737 lambda = 1; f = 433.8866701 Norm of dx 0.049002 ---- Improvement on iteration 7 = 12.358131801 ----------------- f at the beginning of new iteration, 433.8866701244 Predicted improvement: 3.486008985 lambda = 1; f = 429.1245035 Norm of dx 0.03927 ---- Improvement on iteration 8 = 4.762166652 ----------------- f at the beginning of new iteration, 429.1245034721 Predicted improvement: 1.777896593 lambda = 1; f = 427.0065243 Norm of dx 0.038536 ---- Improvement on iteration 9 = 2.117979150 ----------------- f at the beginning of new iteration, 427.0065243226 Predicted improvement: 0.425590733 lambda = 1; f = 426.3546323 lambda = 1.9332; f = 426.0802084 Norm of dx 0.019421 ---- Improvement on iteration 10 = 0.926315913 ----------------- f at the beginning of new iteration, 426.0802084100 Predicted improvement: 0.324551875 lambda = 1; f = 425.4668649 lambda = 1.9332; f = 424.9571337 lambda = 3.7372; f = 424.1343745 lambda = 7.2247; f = 423.1037561 Norm of dx 0.014759 ---- Improvement on iteration 11 = 2.976452317 ----------------- f at the beginning of new iteration, 423.1037560930 Predicted improvement: 1.778892712 lambda = 1; f = 420.1844916 lambda = 1.9332; f = 418.6378159 Norm of dx 0.083276 ---- Improvement on iteration 12 = 4.465940241 ----------------- f at the beginning of new iteration, 418.6378158517 Predicted improvement: 0.675869621 lambda = 1; f = 418.0966376 Norm of dx 0.053371 ---- Improvement on iteration 13 = 0.541178226 ----------------- f at the beginning of new iteration, 418.0966376256 Predicted improvement: 0.132691579 lambda = 1; f = 417.8993765 lambda = 1.9332; f = 417.8314563 Norm of dx 0.015444 ---- Improvement on iteration 14 = 0.265181353 ----------------- f at the beginning of new iteration, 417.8314562724 Predicted improvement: 0.130796421 lambda = 1; f = 417.6028560 lambda = 1.9332; f = 417.4560798 lambda = 3.7372; f = 417.4094975 Norm of dx 0.0079178 ---- Improvement on iteration 15 = 0.421958799 ----------------- f at the beginning of new iteration, 417.4094974730 Predicted improvement: 0.214764507 lambda = 1; f = 417.0908187 lambda = 1.9332; f = 416.9589854 Norm of dx 0.022188 ---- Improvement on iteration 16 = 0.450512033 ----------------- f at the beginning of new iteration, 416.9589854405 Predicted improvement: 0.265928464 lambda = 1; f = 416.4889446 lambda = 1.9332; f = 416.1619586 lambda = 3.7372; f = 415.8389133 Norm of dx 0.032356 ---- Improvement on iteration 17 = 1.120072156 ----------------- f at the beginning of new iteration, 415.8389132848 Predicted improvement: 0.329531131 lambda = 1; f = 415.3433466 lambda = 1.9332; f = 415.1775990 Norm of dx 0.03627 ---- Improvement on iteration 18 = 0.661314273 ----------------- f at the beginning of new iteration, 415.1775990123 Predicted improvement: 0.113857392 lambda = 1; f = 414.9838116 lambda = 1.9332; f = 414.8666119 lambda = 3.7372; f = 414.8294627 Norm of dx 0.0098551 ---- Improvement on iteration 19 = 0.348136284 ----------------- f at the beginning of new iteration, 414.8294627283 Predicted improvement: 0.401531803 lambda = 1; f = 414.1774675 lambda = 1.9332; f = 413.8422289 Norm of dx 0.020242 ---- Improvement on iteration 20 = 0.987233843 ----------------- f at the beginning of new iteration, 413.8422288852 Predicted improvement: 0.461924839 lambda = 1; f = 413.2413900 Norm of dx 0.08425 ---- Improvement on iteration 21 = 0.600838859 ----------------- f at the beginning of new iteration, 413.2413900258 Predicted improvement: 0.177162769 lambda = 1; f = 412.9901622 lambda = 1.9332; f = 412.9495531 Norm of dx 0.052497 ---- Improvement on iteration 22 = 0.291836959 ----------------- f at the beginning of new iteration, 412.9495530666 Predicted improvement: 0.148659983 lambda = 1; f = 412.6679323 lambda = 1.9332; f = 412.4333172 lambda = 3.7372; f = 412.0559288 lambda = 7.2247; f = 411.6055708 Norm of dx 0.0087368 ---- Improvement on iteration 23 = 1.343982240 ----------------- f at the beginning of new iteration, 411.6055708267 Predicted improvement: 1.480013322 lambda = 1; f = 409.0103396 lambda = 1.9332; f = 407.3634084 lambda = 3.7372; f = 407.3919154 Norm of dx 0.1308 ---- Improvement on iteration 24 = 4.242162383 ----------------- f at the beginning of new iteration, 407.3634084438 Predicted improvement: 2.807799717 lambda = 1; f = 407.3707556 lambda = 0.33333; f = 405.9665619 lambda = 0.64439; f = 407.3634916 lambda = 0.4339; f = 405.8339837 Norm of dx 0.47311 ---- Improvement on iteration 25 = 1.529424739 ----------------- f at the beginning of new iteration, 405.8339837047 Predicted improvement: 0.643828596 lambda = 1; f = 405.0862599 Norm of dx 0.041996 ---- Improvement on iteration 26 = 0.747723840 ----------------- f at the beginning of new iteration, 405.0862598648 Predicted improvement: 0.338398401 lambda = 1; f = 404.7400057 Norm of dx 0.037823 ---- Improvement on iteration 27 = 0.346254169 ----------------- f at the beginning of new iteration, 404.7400056956 Predicted improvement: 0.393479364 lambda = 1; f = 404.1270620 lambda = 1.9332; f = 404.2934522 lambda = 1.3017; f = 404.0400136 Norm of dx 0.053008 ---- Improvement on iteration 28 = 0.699992048 ----------------- f at the beginning of new iteration, 404.0400136478 Predicted improvement: 0.869317495 lambda = 1; f = 402.8101857 lambda = 1.9332; f = 402.5827161 Norm of dx 0.054242 ---- Improvement on iteration 29 = 1.457297514 ----------------- f at the beginning of new iteration, 402.5827161339 Predicted improvement: 1.475467115 lambda = 1; f = 402.1063835 lambda = 0.33333; f = 402.0673480 Norm of dx 0.075616 ---- Improvement on iteration 30 = 0.515368101 ----------------- f at the beginning of new iteration, 402.0673480326 Predicted improvement: 1.385555632 lambda = 1; f = 401.6114623 lambda = 0.33333; f = 401.4118967 lambda = 0.64439; f = 401.2591028 Norm of dx 0.10251 ---- Improvement on iteration 31 = 0.808245247 ----------------- f at the beginning of new iteration, 401.2591027859 Predicted improvement: 0.119987348 lambda = 1; f = 401.0901320 lambda = 1.9332; f = 401.0571497 Norm of dx 0.017652 ---- Improvement on iteration 32 = 0.201953073 ----------------- f at the beginning of new iteration, 401.0571497128 Predicted improvement: 0.111836466 lambda = 1; f = 400.8483706 lambda = 1.9332; f = 400.6812270 lambda = 3.7372; f = 400.4386970 lambda = 7.2247; f = 400.3088990 Norm of dx 0.018062 ---- Improvement on iteration 33 = 0.748250708 ----------------- f at the beginning of new iteration, 400.3088990053 Predicted improvement: 0.548817668 lambda = 1; f = 399.2905293 lambda = 1.9332; f = 398.4843945 lambda = 3.7372; f = 397.3348750 lambda = 7.2247; f = 396.8367292 Norm of dx 0.059305 ---- Improvement on iteration 34 = 3.472169764 ----------------- f at the beginning of new iteration, 396.8367292409 Predicted improvement: 0.791020103 lambda = 1; f = 395.9090489 Norm of dx 0.059656 ---- Improvement on iteration 35 = 0.927680318 ----------------- f at the beginning of new iteration, 395.9090489232 Predicted improvement: 0.247260609 lambda = 1; f = 395.7177609 Norm of dx 0.035423 ---- Improvement on iteration 36 = 0.191288029 ----------------- f at the beginning of new iteration, 395.7177608946 Predicted improvement: 0.103723995 lambda = 1; f = 395.5758809 Norm of dx 0.015664 ---- Improvement on iteration 37 = 0.141880017 ----------------- f at the beginning of new iteration, 395.5758808779 Predicted improvement: 0.084275191 lambda = 1; f = 395.4670230 Norm of dx 0.020831 ---- Improvement on iteration 38 = 0.108857906 ----------------- f at the beginning of new iteration, 395.4670229719 Predicted improvement: 0.073758821 lambda = 1; f = 395.3451206 lambda = 1.9332; f = 395.2753381 Norm of dx 0.015702 ---- Improvement on iteration 39 = 0.191684887 ----------------- f at the beginning of new iteration, 395.2753380847 Predicted improvement: 0.223115355 lambda = 1; f = 394.8942198 lambda = 1.9332; f = 394.6334000 lambda = 3.7372; f = 394.3415139 Norm of dx 0.062241 ---- Improvement on iteration 40 = 0.933824204 ----------------- f at the beginning of new iteration, 394.3415138810 Predicted improvement: 0.746139555 lambda = 1; f = 393.6471862 Norm of dx 0.15082 ---- Improvement on iteration 41 = 0.694327722 ----------------- f at the beginning of new iteration, 393.6471861589 Predicted improvement: 0.648528155 lambda = 1; f = 393.4040328 lambda = 0.33333; f = 393.3139517 lambda = 0.64439; f = 393.2091770 Norm of dx 0.16168 ---- Improvement on iteration 42 = 0.438009191 ----------------- f at the beginning of new iteration, 393.2091769684 Predicted improvement: 0.079459863 lambda = 1; f = 393.0967132 lambda = 1.9332; f = 393.0745239 Norm of dx 0.018797 ---- Improvement on iteration 43 = 0.134653020 ----------------- f at the beginning of new iteration, 393.0745239488 Predicted improvement: 0.077439082 lambda = 1; f = 392.9297659 lambda = 1.9332; f = 392.8125721 lambda = 3.7372; f = 392.6333927 lambda = 7.2247; f = 392.4552927 Norm of dx 0.0149 ---- Improvement on iteration 44 = 0.619231216 ----------------- f at the beginning of new iteration, 392.4552927332 Predicted improvement: 0.443660061 lambda = 1; f = 391.7738788 lambda = 1.9332; f = 391.7650649 Norm of dx 0.15888 ---- Improvement on iteration 45 = 0.690227882 ----------------- f at the beginning of new iteration, 391.7650648513 Predicted improvement: 1.473091131 lambda = 1; f = 390.4186297 Norm of dx 0.09456 ---- Improvement on iteration 46 = 1.346435185 ----------------- f at the beginning of new iteration, 390.4186296658 Predicted improvement: 0.438714535 lambda = 1; f = 389.7117183 lambda = 1.9332; f = 389.3950097 Norm of dx 0.071241 ---- Improvement on iteration 47 = 1.023619988 ----------------- f at the beginning of new iteration, 389.3950096782 Predicted improvement: 0.252942179 lambda = 1; f = 389.0828780 Norm of dx 0.030536 ---- Improvement on iteration 48 = 0.312131726 ----------------- f at the beginning of new iteration, 389.0828779523 Predicted improvement: 0.489105707 lambda = 1; f = 388.6430027 Norm of dx 0.18208 ---- Improvement on iteration 49 = 0.439875215 ----------------- f at the beginning of new iteration, 388.6430027378 Predicted improvement: 0.496482780 lambda = 1; f = 388.1838772 Norm of dx 0.082165 ---- Improvement on iteration 50 = 0.459125555 ----------------- f at the beginning of new iteration, 388.1838771824 Predicted improvement: 0.341819135 lambda = 1; f = 388.0225107 lambda = 0.33333; f = 388.0083820 lambda = 0.64439; f = 387.9482135 Norm of dx 0.061972 ---- Improvement on iteration 51 = 0.235663684 ----------------- f at the beginning of new iteration, 387.9482134985 Predicted improvement: 0.263518273 lambda = 1; f = 387.6220632 Norm of dx 0.058751 ---- Improvement on iteration 52 = 0.326150321 ----------------- f at the beginning of new iteration, 387.6220631772 Predicted improvement: 0.231855772 lambda = 1; f = 387.2525857 lambda = 1.9332; f = 387.0986709 Norm of dx 0.073385 ---- Improvement on iteration 53 = 0.523392239 ----------------- f at the beginning of new iteration, 387.0986709382 Predicted improvement: 0.430192036 lambda = 1; f = 386.6780834 Norm of dx 0.12734 ---- Improvement on iteration 54 = 0.420587499 ----------------- f at the beginning of new iteration, 386.6780834394 Predicted improvement: 0.217807109 lambda = 1; f = 386.3268544 lambda = 1.9332; f = 386.1714048 Norm of dx 0.0428 ---- Improvement on iteration 55 = 0.506678612 ----------------- f at the beginning of new iteration, 386.1714048270 Predicted improvement: 0.340417849 lambda = 1; f = 386.2545716 lambda = 0.33333; f = 386.0457594 Norm of dx 0.1114 ---- Improvement on iteration 56 = 0.125645378 ----------------- f at the beginning of new iteration, 386.0457594493 Predicted improvement: 0.100581870 lambda = 1; f = 385.9464145 Norm of dx 0.028817 ---- Improvement on iteration 57 = 0.099344984 ----------------- f at the beginning of new iteration, 385.9464144650 Predicted improvement: 0.014460906 lambda = 1; f = 385.9254028 lambda = 1.9332; f = 385.9196402 Norm of dx 0.01519 ---- Improvement on iteration 58 = 0.026774217 ----------------- f at the beginning of new iteration, 385.9196402476 Predicted improvement: 0.004559153 lambda = 1; f = 385.9135706 Norm of dx 0.010929 ---- Improvement on iteration 59 = 0.006069668 ----------------- f at the beginning of new iteration, 385.9135705793 Predicted improvement: 0.001987888 lambda = 1; f = 385.9109988 Norm of dx 0.0081273 ---- Improvement on iteration 60 = 0.002571752 ----------------- f at the beginning of new iteration, 385.9109988275 Predicted improvement: 0.000813781 lambda = 1; f = 385.9097238 lambda = 1.9332; f = 385.9091637 Norm of dx 0.0038654 ---- Improvement on iteration 61 = 0.001835107 ----------------- f at the beginning of new iteration, 385.9091637203 Predicted improvement: 0.000951911 lambda = 1; f = 385.9073666 lambda = 1.9332; f = 385.9058770 lambda = 3.7372; f = 385.9035114 lambda = 7.2247; f = 385.9008608 Norm of dx 0.0015702 ---- Improvement on iteration 62 = 0.008302913 ----------------- f at the beginning of new iteration, 385.9008608077 Predicted improvement: 0.006680492 lambda = 1; f = 385.8885504 lambda = 1.9332; f = 385.8789389 lambda = 3.7372; f = 385.8654551 lambda = 7.2247; f = 385.8582699 Norm of dx 0.0090324 ---- Improvement on iteration 63 = 0.042590921 ----------------- f at the beginning of new iteration, 385.8582698864 Predicted improvement: 0.015562382 lambda = 1; f = 385.8362793 lambda = 1.9332; f = 385.8318190 Norm of dx 0.01162 ---- Improvement on iteration 64 = 0.026450866 ----------------- f at the beginning of new iteration, 385.8318190201 Predicted improvement: 0.001287081 lambda = 1; f = 385.8300874 Norm of dx 0.00392 ---- Improvement on iteration 65 = 0.001731620 ----------------- f at the beginning of new iteration, 385.8300873996 Predicted improvement: 0.000626463 lambda = 1; f = 385.8292156 Norm of dx 0.0029819 ---- Improvement on iteration 66 = 0.000871774 ----------------- f at the beginning of new iteration, 385.8292156260 Predicted improvement: 0.000353029 lambda = 1; f = 385.8287617 Norm of dx 0.0030729 ---- Improvement on iteration 67 = 0.000453942 ----------------- f at the beginning of new iteration, 385.8287616839 Predicted improvement: 0.000098290 lambda = 1; f = 385.8286224 lambda = 1.9332; f = 385.8285997 Norm of dx 0.0014431 ---- Improvement on iteration 68 = 0.000162010 ----------------- f at the beginning of new iteration, 385.8285996737 Predicted improvement: 0.000053576 lambda = 1; f = 385.8285010 lambda = 1.9332; f = 385.8284233 lambda = 3.7372; f = 385.8283119 lambda = 7.2247; f = 385.8282422 Norm of dx 0.00043831 ---- Improvement on iteration 69 = 0.000357448 ----------------- f at the beginning of new iteration, 385.8282422260 Predicted improvement: 0.000283167 lambda = 1; f = 385.8276816 lambda = 1.9332; f = 385.8271689 lambda = 3.7372; f = 385.8262066 lambda = 7.2247; f = 385.8244544 lambda = 13.967; f = 385.8214738 lambda = 27; f = 385.8172510 lambda = 52.196; f = 385.8149981 Norm of dx 0.00092637 ---- Improvement on iteration 70 = 0.013244163 ----------------- f at the beginning of new iteration, 385.8149980628 Predicted improvement: 0.009701254 lambda = 1; f = 385.7978092 lambda = 1.9332; f = 385.7856787 lambda = 3.7372; f = 385.7727774 Norm of dx 0.025258 ---- Improvement on iteration 71 = 0.042220693 ----------------- f at the beginning of new iteration, 385.7727773696 Predicted improvement: 0.004081527 lambda = 1; f = 385.7689762 Norm of dx 0.037117 ---- Improvement on iteration 72 = 0.003801154 ----------------- f at the beginning of new iteration, 385.7689762151 Predicted improvement: 0.000290852 lambda = 1; f = 385.7687021 Norm of dx 0.0044886 ---- Improvement on iteration 73 = 0.000274120 ----------------- f at the beginning of new iteration, 385.7687020948 Predicted improvement: 0.000014426 lambda = 1; f = 385.7686842 Norm of dx 0.00081274 ---- Improvement on iteration 74 = 0.000017852 ----------------- f at the beginning of new iteration, 385.7686842427 Predicted improvement: 0.000003807 lambda = 1; f = 385.7686774 lambda = 1.9332; f = 385.7686729 lambda = 3.7372; f = 385.7686697 Norm of dx 0.00030986 ---- Improvement on iteration 75 = 0.000014553 ----------------- f at the beginning of new iteration, 385.7686696898 Predicted improvement: 0.000009970 lambda = 1; f = 385.7686501 lambda = 1.9332; f = 385.7686324 lambda = 3.7372; f = 385.7685994 lambda = 7.2247; f = 385.7685407 lambda = 13.967; f = 385.7684462 lambda = 27; f = 385.7683341 Norm of dx 9.8256e-05 ---- Improvement on iteration 76 = 0.000335566 ----------------- f at the beginning of new iteration, 385.7683341242 Predicted improvement: 0.000340514 lambda = 1; f = 385.7677012 lambda = 1.9332; f = 385.7671941 lambda = 3.7372; f = 385.7664421 lambda = 7.2247; f = 385.7658403 Norm of dx 0.004547 ---- Improvement on iteration 77 = 0.002493812 ----------------- f at the beginning of new iteration, 385.7658403117 Predicted improvement: 0.001416069 lambda = 1; f = 385.7634798 lambda = 1.9332; f = 385.7621282 Norm of dx 0.015798 ---- Improvement on iteration 78 = 0.003712148 ----------------- f at the beginning of new iteration, 385.7621281641 Predicted improvement: 0.000587147 lambda = 1; f = 385.7615320 Norm of dx 0.017361 ---- Improvement on iteration 79 = 0.000596157 ----------------- f at the beginning of new iteration, 385.7615320067 Predicted improvement: 0.000000773 lambda = 1; f = 385.7615310 Norm of dx 0.00046916 ---- Improvement on iteration 80 = 0.000001047 ----------------- f at the beginning of new iteration, 385.7615309602 Predicted improvement: 0.000000007 lambda = 1; f = 385.7615310 lambda = 0.33333; f = 385.7615310 lambda = 0.11111; f = 385.7615310 lambda = 0.037037; f = 385.7615310 Norm of dx 2.6639e-05 ---- Improvement on iteration 81 = 0.000000001 improvement < crit termination Final value of minus the log posterior (or likelihood):385.761531 POSTERIOR KERNEL OPTIMIZATION PROBLEM! (minus) the hessian matrix at the "mode" is not positive definite! => posterior variance of the estimated parameters are not positive. You should try to change the initial values of the parameters using the estimated_params_init block, or use another optimization routine. [Warning: The results below are most likely wrong!] [> In dynare_estimation_1 (line 315) In dynare_estimation (line 105) In jp_nk_rkdata.driver (line 300) In dynare (line 293)] MODE CHECK Fval obtained by the minimization routine (minus the posterior/likelihood)): 385.761531 Most negative variance 0.000000 for parameter 15 (mu_y = 0.000000) {Brace indexing is not supported for variables of this type. Error in mode_check (line 202) plot([0.48 0.68],[0.5 0.5],'color',line_color{2}) Error in dynare_estimation_1 (line 322) mode_check(objective_function,xparam1,hh,dataset_,dataset_info,options_,M_,estim_params_,bayestopt_,bounds,oo_); Error in dynare_estimation (line 105) dynare_estimation_1(var_list,dname); Error in jp_nk_rkdata.driver (line 300) oo_recursive_=dynare_estimation(var_list_); Error in dynare (line 293) evalin('base',[fname '.driver']) ; }