The FLStock generated by the call to oem is simply passed on in this function. The estimates of abundance, catches and exploitation will thus be as precise as the OEM observation.
Examples
# Example dataset
data(sol274)
#> Warning: namespace ‘patchwork’ is not available and has been replaced
#> by .GlobalEnv when processing object ‘om’
#> Warning: namespace ‘dplyr’ is not available and has been replaced
#> by .GlobalEnv when processing object ‘om’
#> Warning: namespace ‘TMB’ is not available and has been replaced
#> by .GlobalEnv when processing object ‘om’
#> Warning: namespace ‘remotes’ is not available and has been replaced
#> by .GlobalEnv when processing object ‘om’
#> Warning: namespace ‘shiny’ is not available and has been replaced
#> by .GlobalEnv when processing object ‘om’
#> Warning: namespace ‘htmlwidgets’ is not available and has been replaced
#> by .GlobalEnv when processing object ‘om’
#> Warning: namespace ‘xtable’ is not available and has been replaced
#> by .GlobalEnv when processing object ‘om’
#> Warning: namespace ‘FLAssess’ is not available and has been replaced
#> by .GlobalEnv when processing object ‘om’
#> Warning: namespace ‘FLSRTMB’ is not available and has been replaced
#> by .GlobalEnv when processing object ‘om’
# Sets up an mpCtrl for catch ~ MSY
ctrl <- mpCtrl(est = mseCtrl(method=perfect.sa),
hcr = mseCtrl(method=fixedC.hcr, args=list(ctrg=11400)))
# Runs mp between 2021 and 2035
run <- mp(om, control=ctrl, args=list(iy=2021, fy=2035))
#> 2021 - 2022 - 2023 - 2024 - 2025 - 2026 - 2027 - 2028 - 2029 - 2030 - 2031 - 2032 - 2033 - 2034 -
