SBT1 {DLMtool} | R Documentation |
SBT simple MP
Description
An MP that makes incremental adjustments to TAC recommendations based on the apparent trend in CPUE, a an MP that makes incremental adjustments to TAC recommendations based on index levels relative to target levels (BMSY/B0) and catch levels relative to target levels (MSY).
Usage
SBT1(
x,
Data,
reps = 100,
plot = FALSE,
yrsmth = 10,
k1 = 1.5,
k2 = 3,
gamma = 1
)
SBT2(x, Data, reps = 100, plot = FALSE, epsR = 0.75, tauR = 5, gamma = 1)
Arguments
x |
A position in the data object |
Data |
A data object |
reps |
The number of stochastic samples of the MP recommendation(s) |
plot |
Logical. Show the plot? |
yrsmth |
The number of years for evaluating trend in relative abundance indices |
k1 |
Control parameter |
k2 |
Control parameter |
gamma |
Control parameter |
epsR |
Control parameter |
tauR |
Control parameter |
Details
For SBT1
the TAC is calculated as:
where is the slope of index over the last
yrmsth
years, and
,
, and
are arguments to the MP.
For SBT2
the TAC is calculated as:
where is catch in the previous year,
is a target catch (
Data@Cref
), and :
where is a control parameter and:
where
is mean recruitment over last
tauR
years and
is mean recruitment over last 10 years.
This isn't exactly the same as the proposed methods and is stochastic in this implementation. The method doesn't tend to work too well under many circumstances possibly due to the lack of 'tuning' that occurs in the real SBT assessment environment. You could try asking Rich Hillary at CSIRO about this approach.
Value
An object of class Rec-class
with the TAC
slot populated with a numeric vector of length reps
Functions
-
SBT1
: Simple SBT MP -
SBT2
: Complex SBT MP
Required Data
See Data-class
for information on the Data
object
SBT1
: Cat, Ind, Year
SBT2
: Cat, Cref, Rec
Rendered Equations
See Online Documentation for correctly rendered equations
Author(s)
T. Carruthers
References
http://www.ccsbt.org/site/recent_assessment.php
Examples
SBT1(1, Data=MSEtool::SimulatedData, plot=TRUE)
SBT2(1, Data=MSEtool::SimulatedData, plot=TRUE)