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The r4ss::SStableComparisons() function is useful for producing the tables showing the changes in likelihood by data type that we've shown so far, but it would often be useful to look at the finer scale changes in likelihood by fleet (the table equivalent of Piner Plot vs the main profile plot showing the sum across all fleets).
model Label ALL X1_Comm_Trawl X2_Comm_Fix X3_Rec_WA
194 1 Catch_lambda NA 1.00000e+00 1.00000e+00 1.00000e+00
195 1 Catch_like 6.99642e-10 5.80240e-10 4.13638e-11 2.12453e-11
196 1 Init_equ_lambda NA 1.00000e+00 1.00000e+00 1.00000e+00
197 1 Init_equ_like 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00
198 1 Surv_lambda NA 1.00000e+00 1.00000e+00 1.00000e+00
199 1 Surv_like -1.62875e+02 -1.61206e+01 -1.48465e+01 -5.23057e+01
200 1 Surv_N_use NA 1.70000e+01 1.70000e+01 4.00000e+01
201 1 Surv_N_skip NA 0.00000e+00 0.00000e+00 0.00000e+00
@kellijohnson-NOAA, if you have time at some point, could you work some tidyverse magic to provide a table of changes in likelihood for each fleet for the Survey (really index), Length, and Age data. For these models I think we can ignore all the rows with labels "lambda", "N_use", "N_skip").
This would help us understand how something like removing fixed-gear ages improves the fit to the fixed-gear length as opposed to all length data.
The text was updated successfully, but these errors were encountered:
The
r4ss::SStableComparisons()
function is useful for producing the tables showing the changes in likelihood by data type that we've shown so far, but it would often be useful to look at the finer scale changes in likelihood by fleet (the table equivalent of Piner Plot vs the main profile plot showing the sum across all fleets).The list returned by
r4ss::SSsummarize()
function (as used in https://github.com/iantaylor-NOAA/Lingcod_2021/blob/main/models/model_STAR_requests.R#L31-L37 with model files on Google Drive) includes a data.framelikelihoods_by_fleet
but the format is terrible (it's just rbinding thelikelihoods_by_fleet
table fromSS_output
):@kellijohnson-NOAA, if you have time at some point, could you work some tidyverse magic to provide a table of changes in likelihood for each fleet for the Survey (really index), Length, and Age data. For these models I think we can ignore all the rows with labels "lambda", "N_use", "N_skip").
This would help us understand how something like removing fixed-gear ages improves the fit to the fixed-gear length as opposed to all length data.
The text was updated successfully, but these errors were encountered: