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Testing of various catch standard deviations
We test the following standard deviations on the catch: 0.05, 0.1, 0.5, 0.2 and 0.25.
Exact catch
Non-RE misfit: 1.820
The estimates and trajectories are:
| Num. cohorts | Trajectories | Estimates |
| 4 |  | Non-RE parfile:
- cod.par
../simple_model_sdreport/cod.par is the user-defined function defined from: ../simple_model_sdreport/cod.par
# Number of parameters = 7 Objective function value = -18.7801 Maximum gradient component = 0.000328611
# N0:
0.622791 0.359443 0.298084 0.589102
# q:
0.344332
# logs:
-1.08687795940
# M:
0.286208904677
|
sc = 0.05
RE misfit: 1.882
| Num. cohorts | Trajectories | Estimates |
| 4 |  |
- cod.par
# Number of parameters = 4 Objective function value = -41.3135 Maximum gradient component = 3.18128e-05
# N0:
0.625798 0.360217 0.297445 0.589751
# q:
0.344330
# logs:
-1.08690000000
# M:
0.286210000000
# logscc:
-2.99570000000
# ce:
0.00607677727972 0.0527881327035 0.108236829066 0.0716351134276 0.111304699438 0.248520863778 0.250954553656 0.00507665924228 0.0273474982545 0.0514526137138 0.0791632153292 0.0512822216301 0.172997445434 -0.0326570725038 0.00642843203800 0.0134611094072 0.00822862264096 -0.120526715382 0.0129580571379 -0.0757812682532 -0.0395552748756 0.00444283876465 0.0593327324051 -0.0238705619626 0.00677922350320 0.00217447025335 0.00811096130120 -0.000525125519077
|
sc = 0.1
RE misfit: 1.765
| Num. cohorts | Trajectories | Estimates |
| 4 |  |
- cod.par
# Number of parameters = 4 Objective function value = -39.1030 Maximum gradient component = 6.59749e-07
# N0:
0.626847 0.359398 0.293274 0.586739
# q:
0.344330
# logs:
-1.08690000000
# M:
0.286210000000
# logscc:
-2.30260000000
# ce:
0.00717371386508 0.0623024987881 0.106838500149 -0.00727841853676 0.133422491700 0.438642102107 0.487122821330 0.00557205734436 0.0189230169446 -0.0115898109589 0.0687880035532 0.0546275293727 0.318954924968 -0.0737794027901 0.00392062069876 -0.0281553619299 -0.0767931533848 -0.308320458142 -0.0103735113069 -0.165205557798 -0.0825936963613 0.00558668464994 0.0896514206481 -0.0864720201540 -0.0114903454906 -0.0101960849496 0.00806135028380 -0.00265801930885
|
sc = 0.15
RE misfit: 1.661
| Num. cohorts | Trajectories | Estimates |
| 4 |  |
- cod.par
# Number of parameters = 4 Objective function value = -37.8395 Maximum gradient component = 8.42471e-05
# N0:
0.627756 0.358000 0.287267 0.580884
# q:
0.344330
# logs:
-1.08690000000
# M:
0.286210000000
# logscc:
-1.89710000000
# ce:
0.00874495514757 0.0760265461654 0.115882157306 -0.0707826286747 0.151430209660 0.611123044389 0.717677634190 0.00681978747091 0.0169088880577 -0.0517818229251 0.0740424294426 0.0625218779776 0.463932951854 -0.114733356896 0.00297546617756 -0.0567185172784 -0.129556977585 -0.449898032102 -0.00965238424925 -0.231960325692 -0.114328666724 0.00485844416478 0.105422304293 -0.163748016705 -0.0380416440742 -0.0255873228041 0.00740885850240 -0.00459962718646
|
sc = 0.20
RE misfit: 1.543
| Num. cohorts | Trajectories | Estimates |
| 4 |  |
- cod.par
# Number of parameters = 4 Objective function value = -37.0410 Maximum gradient component = 7.82529e-08
# N0:
0.628473 0.356175 0.280516 0.573662
# q:
0.344330
# logs:
-1.08690000000
# M:
0.286210000000
# logscc:
-1.60940000000
# ce:
0.0105945326672 0.0924150565958 0.131672733003 -0.122988529089 0.160092228320 0.754206722089 0.932703965414 0.00833505245764 0.0176928559663 -0.0801478682914 0.0857703374823 0.0690610265861 0.601980358685 -0.156020358537 0.00299342620150 -0.0754628415649 -0.155311268816 -0.548969360875 0.0133179595988 -0.276253970069 -0.134205773273 0.00439542206215 0.127236667450 -0.225951783363 -0.0529266402812 -0.0313054265443 0.0140114328999 -0.00454072712752
|
sc = 0.25
RE misfit: 1.420
| Num. cohorts | Trajectories | Estimates |
| 4 |  |
- cod.par
# Number of parameters = 4 Objective function value = -36.4879 Maximum gradient component = 0.000174743
# N0:
0.628747 0.354038 0.273783 0.565967
# q:
0.344330
# logs:
-1.08690000000
# M:
0.286210000000
# logscc:
-1.38630000000
# ce:
0.0125564588907 0.110250222202 0.151499565938 -0.166635957021 0.158328129982 0.861012158619 1.11894581604 0.00996117587657 0.0201967149377 -0.0998994921814 0.101236517714 0.0722938204005 0.728453096543 -0.196792494711 0.00360153715761 -0.0867820061536 -0.159657096149 -0.613204271138 0.0543741927850 -0.301492912920 -0.143405877135 0.00427958102293 0.156243372877 -0.271969861788 -0.0555966832440 -0.0271598469491 0.0279294136297 -0.00242007305686
|
