MPs that perform worse than comparable MPs across all performance metrics are considered 'dominated' as other options are always preferable.
Arguments
- MSEobj
An object of class
MSE- ...
Names of Performance Metrics (PMs), or other arguments to
TradePlot. First PM is recycled if number of PMs is not even- PMlist
Optional list of PM names. Overrides any supplied in ... above
- Refs
An optional named list (matching the PM names) with numeric values to override the default
Refvalues.- Yrs
An optional named list (matching the PM names) with numeric values to override the default
Yrsvalues.
Value
A named list of length 2 with a character vector of non-dominated MPs in MPs and
a data.frame of dominated MPs and the names of the relevant dominated MPs in DomMPs
Details
The Dom function compares the probabilities calculated in the performance metric
(PM) functions and determines the MPs that have a lower probability across all PMs compared
to other MPs of the same management type (e.g., size limit, TAC, etc).
Consequently, it is important that all PM functions are constructed so that higher probabilities = better performance
(e.g, PNOF is the probability of NOT overfishing)
Examples
if (FALSE) { # \dontrun{
MSE <- runMSE(MPs=NA) # run all MPs
Nondom <- Dom(MSE, "P10", "LTY", "PNOF")
# Non-dominated MPs
Nondom$MPs
# Dominated MPs
Nondom$DomMPs
} # }