You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Adding the Pstar buffer to your forecast file using PEPtools::get_buffer()
default sigma input to that function is 0.5 for Category 1 stocks and 1.0 for Cat 2 but if uncertainty in model (either model$Pstar_sigma or model$OFL_sigma?) is larger, use that instead.
pstar input is set by the council (check with GMT rep)
Make sure you are using 3 # Control rule method (0: none; 1: ramp does catch=f(SSB), buffer on F; 2: ramp does F=f(SSB), buffer on F; 3: ramp does catch=f(SSB), buffer on catch; 4: ramp does F=f(SSB), buffer on catch)
Inspired by chat with @okenk and @chantelwetzel-noaa. Please edit this list as needed.
Documentation needed for things like
sigma
input to that function is 0.5 for Category 1 stocks and 1.0 for Cat 2 but if uncertainty in model (eithermodel$Pstar_sigma
ormodel$OFL_sigma
?) is larger, use that instead.pstar
input is set by the council (check with GMT rep)3 # Control rule method (0: none; 1: ramp does catch=f(SSB), buffer on F; 2: ramp does F=f(SSB), buffer on F; 3: ramp does catch=f(SSB), buffer on catch; 4: ramp does F=f(SSB), buffer on catch)
r4ss::SSexecutivesummar()
does most of the work.SSexecutivesummary(model, forecast_ofl = c(3763, 3563))
The text was updated successfully, but these errors were encountered: