A simple age-structured model (SCA_Pope) fitted to a time series of catch going back to unfished conditions.
Terminal depletion (ratio of current total biomass to unfished biomass) is by default fixed to 0.4. Selectivity is fixed
to the maturity ogive, although it can be overridden with the start argument. The sole parameter estimated is
R0 (unfished recruitment), with no process error.

```
SSS(
x = 1,
Data,
dep = 0.4,
SR = c("BH", "Ricker"),
rescale = "mean1",
start = NULL,
silent = TRUE,
opt_hess = FALSE,
n_restart = ifelse(opt_hess, 0, 1),
control = list(iter.max = 2e+05, eval.max = 4e+05),
...
)
```

## Arguments

- x
A position in the Data object (by default, equal to one for assessments).

- Data
An object of class Data

- dep
Depletion value to use in the model. Can be an expression that will be evaluated inside the function.

- SR
Stock-recruit function (either `"BH"`

for Beverton-Holt or `"Ricker"`

).

- rescale
A multiplicative factor that rescales the catch in the assessment model, which
can improve convergence. By default, `"mean1"`

scales the catch so that time series mean is 1, otherwise a numeric.
Output is re-converted back to original units.

- start
Optional named list of starting values. Entries can be expressions that are evaluated in the function:

- silent
Logical, passed to `MakeADFun`

, whether TMB
will print trace information during optimization. Used for diagnostics for model convergence.

- opt_hess
Logical, whether the hessian function will be passed to `nlminb`

during optimization
(this generally reduces the number of iterations to convergence, but is memory and time intensive and does not guarantee an increase
in convergence rate).

- n_restart
The number of restarts (calls to `nlminb`

) in the optimization procedure, so long as the model
hasn't converged. The optimization continues from the parameters from the previous (re)start.

- control
A named list of arguments for optimization to be passed to `nlminb`

.

- ...
Other arguments to be passed (not currently used).

## Details

In SAMtool, SSS is an implementation of SCA_Pope with fixed final depletion
(in terms of total biomass, not spawning biomass) assumption.

## References

Cope, J.M. 2013. Implementing a statistical catch-at-age model (Stock Synthesis) as a tool for
deriving overfishing limits in data-limited situations. Fisheries Research 142:3-14.

## Examples

```
res <- SSS(Data = Red_snapper)
SSS_MP <- make_MP(SSS, HCR40_10, dep = 0.3) # Always assume depletion = 0.3
```