library(fishvice)
rbx <- mup_rbx("/u2/reikn/Tac/2022/01-cod/ass/mup/smx")
rbx
#> $rby
#> # A tibble: 73 × 23
#> year fbar hr pY oY ssb eggp bio2 bio1 bio
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1955 0.348 0.261 539. 545. 726. 27.9 1622. 1671. 2090.
#> 2 1956 0.346 0.268 462. 487. 584. 21.9 1416. 1466. 1818.
#> 3 1957 0.387 0.278 454. 455. 575. 21.6 1259. 1339. 1640.
#> 4 1958 0.436 0.313 508. 517. 690. 25.3 1243. 1373. 1650.
#> 5 1959 0.384 0.290 437. 459. 639. 24.0 1219. 1300. 1580.
#> 6 1960 0.428 0.284 475. 470. 584. 21.8 1264. 1331. 1658.
#> 7 1961 0.401 0.264 388. 377. 399. 13.6 1104. 1055. 1431.
#> 8 1962 0.403 0.266 394. 389. 505. 18.5 1130. 1174. 1464.
#> 9 1963 0.460 0.315 408. 409. 460. 17.4 974. 1059. 1299.
#> 10 1964 0.521 0.361 417. 437. 420. 16.8 890. 979. 1211.
#> # ℹ 63 more rows
#> # ℹ 13 more variables: PredictedRecruitment <dbl>, r <dbl>, N1st <dbl>,
#> # N3 <dbl>, N6 <dbl>, pU1 <dbl>, oU1 <dbl>, pU2 <dbl>, oU2 <dbl>, hr2 <dbl>,
#> # run <chr>, model <chr>, assyear <dbl>
#>
#> $rbya
#> # A tibble: 1,022 × 23
#> year age n f oC pC rC cW ssbW sW mat
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1955 1 240881 NA NA NA NA NA NA 15 NA
#> 2 1955 2 175583 NA NA NA NA NA NA 141 NA
#> 3 1955 3 151014 0.0623 4790 8278. -0.487 827 645 250 0.019
#> 4 1955 4 211538 0.177 25164 31180. -0.209 1307 1019 588 0.022
#> 5 1955 5 199652 0.240 46566 38758. 0.180 2157 1833 1439 0.033
#> 6 1955 6 110948 0.250 28287 22374. 0.228 3617 3183 2901 0.181
#> 7 1955 7 31896. 0.310 10541 7741. 0.284 4638 4128 3923 0.577
#> 8 1955 8 20440. 0.372 5224 5789. -0.0900 5657 5657 4944 0.782
#> 9 1955 9 9573. 0.414 2467 2960. -0.142 6635 6635 5923 0.834
#> 10 1955 10 77118. 0.500 25182 27712. -0.0930 6168 6168 6168 0.96
#> # ℹ 1,012 more rows
#> # ℹ 12 more variables: m <dbl>, z <dbl>, pU1 <dbl>, oU1 <dbl>, rU1 <dbl>,
#> # pU2 <dbl>, oU2 <dbl>, rU2 <dbl>, run <chr>, model <chr>, assyear <dbl>,
#> # yc <dbl>
#>
#> $rba
#> # A tibble: 14 × 12
#> age meansel progsel SigmaC sigmaU1 qU1 pU1 sigmaU2 qU2 pU2
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 NA NA NA 0.414 6.76e-16 3 NA 1 e+0 1
#> 2 2 NA NA NA 0.267 1.79e-11 2.30 NA 1 e+0 1
#> 3 3 0.106 0.0908 0.229 0.248 1.67e-10 2.19 0.242 1.12e-9 2.01
#> 4 4 0.358 0.283 0.182 0.264 1.15e- 9 2.08 0.268 2.20e-9 2.01
#> 5 5 0.586 0.502 0.155 0.217 6.57e- 8 1.78 0.194 8.41e-7 1.53
#> 6 6 0.780 0.811 0.139 0.162 6.35e- 6 1.41 0.162 5.85e-5 1.18
#> 7 7 0.977 0.989 0.133 0.156 1.75e- 5 1.36 0.179 1.69e-4 1.09
#> 8 8 1.16 1.22 0.134 0.170 8.69e- 5 1.22 0.223 2.17e-4 1.09
#> 9 9 1.21 1.21 0.144 0.194 2.46e- 4 1.11 0.236 2.87e-4 1.06
#> 10 10 1.29 1.27 0.165 0.211 6.45e- 4 1 0.238 4.69e-4 1
#> 11 11 1.30 1.26 0.199 0.211 6.45e- 4 1 0.238 4.69e-4 1
#> 12 12 1.35 1.59 0.256 0.211 6.45e- 4 1 0.238 4.69e-4 1
#> 13 13 1.35 1.59 0.350 0.211 6.45e- 4 1 0.238 4.69e-4 1
#> 14 14 1.35 1.59 0.508 0.211 6.45e- 4 1 NA 1 e+0 1
#> # ℹ 2 more variables: run <chr>, model <chr>
#>
#> $opr
#> # A tibble: 3,358 × 8
#> year age run assyear fleet o p r
#> <dbl> <dbl> <chr> <dbl> <chr> <dbl> <dbl> <dbl>
#> 1 1955 1 smx 2022 catch NA NA NA
#> 2 1955 2 smx 2022 catch NA NA NA
#> 3 1955 3 smx 2022 catch 8.47 9.02 -0.487
#> 4 1955 4 smx 2022 catch 10.1 10.3 -0.209
#> 5 1955 5 smx 2022 catch 10.7 10.6 0.180
#> 6 1955 6 smx 2022 catch 10.3 10.0 0.228
#> 7 1955 7 smx 2022 catch 9.26 8.95 0.284
#> 8 1955 8 smx 2022 catch 8.56 8.66 -0.0900
#> 9 1955 9 smx 2022 catch 7.81 7.99 -0.142
#> 10 1955 10 smx 2022 catch 10.1 10.2 -0.0930
#> # ℹ 3,348 more rows
#>
#> $std
#> # A tibble: 469 × 4
#> index name value std.dev
#> <int> <chr> <dbl> <dbl>
#> 1 1 logdeltaQ1March 0.655 0.133
#> 2 2 lnMigrationAbundance 9.37 0.365
#> 3 3 lnMigrationAbundance 9.63 0.455
#> 4 4 lnMigrationAbundance 9.31 0.478
#> 5 5 lnMigrationAbundance 9.73 0.158
#> 6 6 lnMigrationAbundance 1 0.0515
#> 7 7 lnMigrationAbundance 10.3 0.134
#> 8 8 lnMigrationAbundance 9.52 0.245
#> 9 9 lnMigrationAbundance 9.70 0.159
#> 10 10 lnMigrationAbundance 8.61 2.37
#> # ℹ 459 more rows
#>
#> $par
#> $par$obj
#> npar objective max_gradient
#> 2.500000e+02 -2.079749e+03 7.622921e-05
#>
#> $par$logdeltaQ1March
#> [1] 0.6551629
#>
#> $par$logMisreportingRatio
#> [1] 0
#>
#> $par$logFoldestmult
#> [1] 0
#>
#> $par$logMoldest
#> [1] -1.6
#>
#> $par$logMmultiplier
#> [1] 0
#>
#> $par$lnMigrationAbundance
#> [1] 9.370119 9.634295 9.307920 9.730100 1.000015 10.312765 9.518669
#> [8] 9.703629 8.609403 9.038309 10.302203 8.622908
#>
#> $par$lnMeanRecr
#> [1] 12.37946
#>
#> $par$lnRecr
#> [1] 0.01259485 0.29940208 0.64578637 -0.03700625 0.20603841 -0.24218922
#> [7] 0.08281672 0.21439603 0.32014709 0.37953902 0.69765182 0.07081169
#> [13] 0.40732273 0.11847460 0.19099492 -0.11665855 0.55509592 0.15945558
#> [19] 0.48622549 0.84380867 -0.10150117 0.34500331 0.40647507 -0.12051210
#> [25] -0.08939176 -0.13464360 0.36799133 -0.12716708 -0.13541702 0.64647032
#> [31] 0.45935383 0.09831486 -0.50265100 -0.19610370 -0.34132278 0.06675745
#> [37] -0.23413941 -0.67280424 -0.09189857 0.00540316 -0.52903228 -0.00489500
#> [43] -0.73519837 0.01927540 -0.05823278 -0.01648118 0.08996608 -0.58983630
#> [49] -0.06135616 -0.19745639 -0.48809334 -0.22269369 -0.32491044 -0.23599646
#> [55] 0.04994250 0.11650714 -0.20947094 0.05919857 -0.10594622 -0.51803713
#> [61] -0.06672524 -0.02366625 -0.38177254 -0.11709019 -0.21142897 0.11805725
#> [67] -0.07537884 -0.22217310
#>
#> $par$lnMeanInitialpop
#> [1] 10.31795
#>
#> $par$lnInitialpop
#> [1] 1.75792258 1.60718174 1.94421215 1.88638439 1.29886866 0.05230127
#> [7] -0.39268604 -1.15124969 0.93515187 -1.55837586 -1.86119297 -1.70698461
#> [13] -2.81153346
#>
#> $par$EstimatedSelection
#> [,1] [,2] [,3] [,4]
#> [1,] -2.13362866 -2.70820358 -3.077679264 -2.8646891
#> [2,] -1.09029299 -1.10686633 -1.742390685 -1.7282283
#> [3,] -0.78553741 -0.54541822 -0.952375789 -1.1543171
#> [4,] -0.74259609 -0.18718634 -0.548053579 -0.6746539
#> [5,] -0.53005322 0.04817375 -0.294972234 -0.4763505
#> [6,] -0.34747714 0.19999966 -0.163962647 -0.2628952
#> [7,] -0.24064591 0.17529451 -0.064880416 -0.2781562
#> [8,] -0.05220447 0.12500737 -0.007185597 -0.2286255
#> [9,] 0.06417325 -0.05901586 0.017562472 -0.2344359
#>
#> $par$Catchlogitslope
#> [1] 1
#>
#> $par$Catchlogitage50
#> [1] 5
#>
#> $par$selslope
#> [1] 2.6
#>
#> $par$fullselwt
#> [1] 1750
#>
#> $par$logSigmaCmultiplier
#> [1] 0.2366006
#>
#> $par$AbundanceMultiplier
#> [1] 0
#>
#> $par$lnMeanEffort
#> [1] -0.3383914
#>
#> $par$lnEffort
#> [1] -0.303400505 -0.307881151 -0.196185549 -0.077660869 -0.204299582
#> [6] -0.094129934 -0.159229073 -0.155004073 -0.023538863 0.101046365
#> [11] 0.178727448 0.098184057 0.026047028 0.182136359 -0.028304031
#> [16] 0.182275202 0.360074955 0.354726140 0.405799845 0.436406986
#> [21] 0.427129399 -0.006670291 -0.216935469 -0.430938273 -0.485064720
#> [26] -0.385535597 -0.145282892 -0.014402116 -0.081272923 -0.151120387
#> [31] -0.035784184 0.159215870 0.216780360 0.236714124 0.043068195
#> [36] 0.057167815 0.232355574 0.338544779 0.318969144 -0.069895748
#> [41] 0.082457676 0.033179574 0.055360370 0.246381006 0.407265252
#> [46] 0.421833861 0.340963938 0.150150016 0.128129248 0.191541365
#> [51] 0.147128925 0.093157912 0.009806820 -0.139026390 -0.068336341
#> [56] -0.232207749 -0.302101686 -0.284992753 -0.208760778 -0.317258438
#> [61] -0.359848390 -0.336398024 -0.332350853 -0.252068287 -0.157105560
#> [66] -0.035220213 -0.064513916
#>
#> $par$meanlogSurvivors
#> [1] 13
#>
#> $par$logSurvivors
#> [1] 0 0 0 0 0 0 0 0 0 0 0 0 0
#>
#> $par$SurveyPowerest
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
#> [1,] 3.000000 2.303628 2.189561 2.079890 1.780958 1.409767 1.356043 1.220812
#> [2,] 2.000276 2.000276 2.012178 2.010661 1.530137 1.181119 1.094731 1.086668
#> [,9] [,10]
#> [1,] 1.113046 2.000276
#> [2,] 1.062055 2.000276
#>
#> $par$surveybiopow1
#> [1] 1
#>
#> $par$surveybiopow2
#> [1] 1
#>
#> $par$SigmaSurveypar
#> [1] -0.3519848 -0.2626181
#>
#> $par$SurveylnQest
#> [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] -34.9301429 -24.7437754 -22.51541 -20.58427 -16.53858 -11.967399
#> [2,] -0.6893003 -0.6893003 -20.61289 -19.93345 -13.98870 -9.746938
#> [,7] [,8] [,9] [,10]
#> [1,] -10.953542 -9.351203 -8.310686 -7.345710
#> [2,] -8.686187 -8.435497 -8.157412 -7.665411
#>
#> $par$surveylogitslope
#> [1] 2 2
#>
#> $par$surveylogitage50
#> [1] 1 1
#>
#> $par$Surveycorr1
#> [1] 0.4613425
#>
#> $par$Surveycorr2
#> [1] 0.6710178
#>
#> $par$logSigmaSurvey
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14]
#> [1,] -2.8 -2.8 -2.8 -2.8 -2.8 -2.8 -2.8 -2.8 -2.8 -2.8 -2.8 -2.8 -2.8 -2.8
#> [2,] -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0
#>
#> $par$logSigmaSurveybio
#> [1] -1.150026 -1.150026
#>
#> $par$estSSBRecParameters1
#> [1] 12.60317
#>
#> $par$estSSBRecParameters2
#> [1] 4.787492
#>
#> $par$estSSBRecParameters3
#> [1] -1.339013
#>
#> $par$estSSBRecParameters4
#> [1] -2.302585
#>
#> $par$estSSBRecParameters5
#> [1] 0.01
#>
#> $par$estSSBRecParameters6
#> [1] 1750
