An MP that makes incremental adjustments to TAC recommendations based on the apparent trend in surplus production. Based on the theory of Mark Maunder (IATTC)
SPmod(x, Data, reps = 100, plot = FALSE, alp = c(0.8, 1.2), bet = c(0.8, 1.2))An object of class Rec-class with the TAC slot populated with a numeric vector of length reps
A numeric vector of TAC recommendations
A position in the data object
A data object
The number of stochastic samples of the MP recommendation(s)
Logical. Show the plot?
Condition for modifying the TAC (bounds on change in abundance)
Limits for how much the TAC can change among years
See Data-class for information on the Data object
SPmod: Cat, Ind
See Online Documentation for correctly rendered equations
T. Carruthers
Note that this isn't exactly what Mark has previously suggested and is stochastic in this implementation.
The TAC is calculated as:
$$\textrm{TAC}_y =
\left\{\begin{array}{ll}
C_{y-1} \textrm{bet}_1 & \textrm{if } r < \alpha_1 \\
C_{y-1} & \textrm{if } \alpha_1 < r < \alpha_2 \\
\textrm{bet}_2 (b_2 - b_1 + C_{y-2} ) & \textrm{if } r > \alpha_2 \\
\end{array}\right.
$$
where \(\textrm{bet}_1\) and \(\textrm{bet}_2\) are elements in bet,
\(r\) is the ratio of the index in the most recent two years, \(C_{y-1}\)
is catch in the previous year, \(b_1\) and \(b_2\) are ratio of index
in \(y-2\) and \(y-1\) over the estimate of catchability \(\left(\frac{I}{A}\right)\),
and \(\alpha_1\), \(\alpha_2\), and \(\alpha_3\) are specified in argument
alp.
http://www.iattc.org/Meetings/Meetings2014/MAYSAC/PDFs/SAC-05-10b-Management-Strategy-Evaluation.pdf
Other Surplus production MPs:
Fadapt(),
Rcontrol(),
SPMSY(),
SPSRA(),
SPslope()
SPmod(1, Data=MSEtool::Atlantic_mackerel, plot=TRUE)
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