Conditioning with Life-History Information

By default, the life-history information provided to the Management Procedures is determined by the real life-history values specified in the OM (e.g., OM@Linf) and the bias specified in the observation model.

For example:

OM <- new('OM', Albacore, Generic_IncE, Generic_Obs, Perfect_Imp, nsim=4)
Hist <- Simulate(OM, silent=TRUE)

# OM Linf values in last historical year
## [1] 128.9126 127.0029 130.6198 131.4645
# Linf values provided to MP in this year (ie in simulated Data)
## [1] 131.5341 126.8888 131.0243 137.1029
# Observation error applied to OM values
Hist@SampPars$Stock$Linfarray[,OM@nyears] * Hist@SampPars$Obs$Linfbias
## [1] 131.5341 126.8888 131.0243 137.1029

Users can provide specific values for the life-history parameters by including them in the Data object. We demonstrate here with Linf, but the same concept applies for all life-history parameters (M, K, L50, etc).

Add Life-History Data to OM

Create a blank Data object:

Data <- new('Data')

Add our ’observedvalues forLinf` - i.e., the values we wish to provide to the MPs:

Data@vbLinf <- 100

Add Data to OM:

OM@cpars$Data <- Data

Simulate the spool-up period (now with Data included in the OM):

Hist <- Simulate(OM, silent=TRUE)

Our ‘observed’ life-history parameters are now provided to the MPs:

## [1] 100 100 100 100

Similar to conditioning with other data, when real life-history values are provided in the Data object, the observation parameters (e.g., Obs@Linfbiascv) are ignored.