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']) ;
}