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Testing of various catch standard deviations
For the model with latent variables for the catch data, we conduct the following experiments. First, the model without latent variables is run. The values for the catchability, standard deviation of the survey indices and the mortality are used as constants in the model with latent variables, which is run for various levels on the standard deviation of the catch data.
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
|
