simulate-methods.RdSimulation methods for a4a stock assessment fits.
simulate(object, nsim = 1, seed = NULL, ...)
# S4 method for class 'a4aFitSA'
simulate(object, nsim = 1, seed = NULL, empirical = TRUE, obserror = FALSE)
# S4 method for class 'SCAPars'
simulate(object, nsim = 1, seed = NULL, empirical = TRUE)
# S4 method for class 'a4aStkParams'
simulate(object, nsim = 1, seed = NULL, empirical = TRUE)
# S4 method for class 'submodels'
simulate(object, nsim = 1, seed = NULL, empirical = TRUE)
# S4 method for class 'submodel'
simulate(object, nsim = 1, seed = NULL, empirical = TRUE)data(ple4)
data(ple4.index)
fmodel <- ~factor(age) + factor(year)
qmodel <- list(~factor(age))
fit1 <- sca(fmodel=fmodel, qmodel=qmodel, stock=ple4, indices=FLIndices(ple4.index))
fit1
#> a4a model fit for: PLE
#>
#> Call:
#> .local(stock = stock, indices = indices, fmodel = ..1, qmodel = ..2)
#>
#> Time used:
#> Pre-processing Running a4a Post-processing Total
#> 0.14269233 1.37771249 0.03404522 1.55445004
#>
#> Submodels:
#> fmodel: ~factor(age) + factor(year)
#> srmodel: ~factor(year)
#> n1model: ~s(age, k = 3)
#> qmodel:
#> BTS-Combined (all): ~factor(age)
#> vmodel:
#> catch: ~s(age, k = 3)
#> BTS-Combined (all): ~1
summary(fit1)
#> An object of class "a4aFitSA"
#>
#> Name: PLE
#> Description: Plaice in IV. ICES WGNSSK 2018. FLAAP
#> Quant: age
#> Dims: age year unit season area iter
#> 10 61 1 1 1 1
#>
#> Range: min max pgroup minyear maxyear minfbar maxfbar
#> 1 10 10 1957 2017 2 6
#>
stock.n(fit1)
#> An object of class "FLQuant"
#> , , unit = unique, season = all, area = unique
#>
#> year
#> age 1957 1958 1959 1960 1961 1962 1963 1964 1965
#> 1 473838 701921 859864 780080 841326 596230 620993 2640249 728827
#> 2 345321 389772 567538 685314 618716 668174 472961 487965 2057493
#> 3 248716 259058 282673 400116 478558 433175 466717 324268 329133
#> 4 178377 173026 171865 180239 251730 302178 272633 286172 194325
#> 5 126843 123615 114268 109023 112792 158114 189175 166215 170460
#> 6 89158 87978 81719 72569 68307 70929 99103 115480 99141
#> 7 61879 62217 58580 52320 45851 43314 44832 61044 69539
#> 8 42452 44471 42892 39004 34430 30270 28513 28845 38495
#> 9 28876 31532 31875 29841 26865 23779 20855 19263 19155
#> 10 19558 34689 44401 48590 48857 47045 43648 38560 33844
#> year
#> age 1966 1967 1968 1969 1970 1971 1972 1973 1974
#> 1 610747 421925 386389 596409 603691 399390 348898 1345589 1017694
#> 2 569304 482263 335495 306974 471849 476060 313061 269547 1019845
#> 3 1394248 394093 338444 235048 213303 325779 324818 207597 172138
#> 4 198530 866504 249673 213912 146856 132080 198405 190062 115226
#> 5 116519 122704 546097 156975 132926 90429 79973 115352 104739
#> 6 102345 72104 77422 343747 97663 81953 54825 46562 63670
#> 7 60086 63887 45873 49141 215706 60744 50143 32244 25993
#> 8 44103 39118 42299 30309 32142 139983 38851 30966 19012
#> 9 25688 30099 27085 29235 20767 21875 94091 25341 19413
#> 10 31479 35795 42102 43415 45190 39748 36896 83504 56853
#> year
#> age 1975 1976 1977 1978 1979 1980 1981 1982 1983
#> 1 698845 548566 778479 640981 704057 924266 931736 1847652 1298487
#> 2 763211 527449 417317 589503 478538 518558 676092 680952 1357953
#> 3 637885 483395 339318 266048 365468 288876 308838 401960 409349
#> 4 92797 349978 271077 187879 141651 187450 145387 155054 204960
#> 5 61646 50541 194885 149016 99256 72051 93532 72364 78399
#> 6 56130 33629 28188 107304 78861 50580 36020 46644 36658
#> 7 34532 30977 18965 15698 57489 40719 25632 18210 23944
#> 8 14939 20156 18430 11158 8924 31631 22035 13841 9968
#> 9 11661 9285 12734 11533 6780 5273 18425 12812 8142
#> 10 38891 26050 18859 17450 15380 10934 7904 14797 14410
#> year
#> age 1984 1985 1986 1987 1988 1989 1990 1991 1992
#> 1 1206091 1644326 3960903 1860346 1839953 1352882 1185562 1052308 916723
#> 2 959194 889540 1201510 2858362 1326880 1304527 964011 852854 758827
#> 3 824510 580594 528659 696764 1619851 743177 737889 555573 493855
#> 4 211670 424498 291336 256305 327070 747967 347935 354641 268802
#> 5 105115 108079 211172 139957 119159 149540 346806 165676 170015
#> 6 40281 53771 53869 101654 65207 54600 69486 165479 79588
#> 7 19080 20877 27169 26309 48086 30348 25761 33645 80654
#> 8 13269 10533 11268 14229 13394 24131 15415 13389 17589
#> 9 5925 7862 6122 6382 7866 7313 13313 8673 7571
#> 10 11466 8735 8566 7173 6574 7125 7094 10883 9640
#> year
#> age 1993 1994 1995 1996 1997 1998 1999 2000 2001
#> 1 617155 637103 996786 978696 3186326 1127019 918089 964100 610284
#> 2 655004 436955 451386 705623 680833 2157480 754317 626357 675855
#> 3 431531 365862 244394 252047 380719 348328 1078941 391700 343095
#> 4 232956 198496 168606 112366 110439 154835 137206 448038 175308
#> 5 125589 106096 90574 76754 48714 44390 60249 56328 198460
#> 6 79603 57324 48518 41323 33354 19631 17320 24797 25008
#> 7 37830 36908 26628 22486 18261 13693 7809 7258 11190
#> 8 41238 18920 18489 13312 10777 8199 5978 3571 3544
#> 9 9759 22451 10315 10063 6988 5349 3973 3014 1904
#> 10 8272 8854 16572 12294 10082 7033 5015 3842 3137
#> year
#> age 2002 2003 2004 2005 2006 2007 2008 2009 2010
#> 1 1693796 509232 992838 608791 624076 1071216 918743 875219 1202850
#> 2 429740 1176824 351801 698940 440434 461421 804427 700680 678463
#> 3 373477 231296 626359 194310 407329 267893 289367 520051 467748
#> 4 155459 163084 99428 283612 94860 211148 144951 163393 307162
#> 5 78631 67161 69343 44565 137207 48773 113388 81283 95904
#> 6 89216 34051 28626 31151 21603 70674 26235 63682 47776
#> 7 11424 39292 14766 13068 15318 11272 38472 14896 37802
#> 8 5523 5459 18519 7284 6885 8507 6500 23028 9275
#> 9 1908 2892 2825 9964 4147 4101 5232 4128 15126
#> 10 2266 1883 2279 2486 7103 5751 5345 6130 6035
#> year
#> age 2011 2012 2013 2014 2015 2016 2017
#> 1 1502024 1354188 1658682 1961517 1171849 1687998 2283111
#> 2 943988 1187249 1075766 1329902 1594711 969047 1421171
#> 3 464014 654770 831645 767388 974951 1208821 760968
#> 4 285811 289187 413743 539093 516870 688194 896622
#> 5 186610 177153 181774 266888 361532 363518 508966
#> 6 58339 115807 111484 117382 179156 254475 269022
#> 7 29328 36518 73486 72550 79337 126831 189193
#> 8 24248 19141 24123 49642 50683 57749 96416
#> 9 6250 16583 13227 16992 35988 38059 45009
#> 10 13947 12237 18891 20766 25552 44558 61496
#>
#> units: 1000