In beta testing. A function that uses RCM as an assessment function for use in MPs. More function arguments will be added
to tinker with model settings and data inputs.

```
RCM_assess(
x = 1,
Data,
AddInd = "B",
SR = c("BH", "Ricker"),
selectivity = c("logistic", "dome"),
CAA_multiplier = 50,
prior = list(),
LWT = list(),
StockPars = "Data",
...
)
```

## Arguments

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

- Data
An object of class Data

- AddInd
A vector of integers or character strings indicating the indices to be used in the model. Integers assign the index to
the corresponding index in Data@AddInd, "B" (or 0) represents total biomass in Data@Ind, "VB" represents vulnerable biomass in
Data@VInd, and "SSB" represents spawning stock biomass in Data@SpInd. Vulnerability to the survey is fixed in the model.

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

for Beverton-Holt or `"Ricker"`

).

- selectivity
Whether to model "logistic" or "dome" selectivity for the fishery.

- CAA_multiplier
Numeric for data weighting of catch-at-age matrix. If greater than 1, then this is the maximum multinomial sample size
in any year. If less than one, then the multinomial sample size is this fraction of the sample size.

- prior
A named list for the parameters of any priors to be added to the model. See documentation in SCA.

- LWT
A named list (Index, CAA, Catch) of likelihood weights for the data components. For the index, a vector of length survey. For
CAL and Catch, a single value.

- StockPars
Either a string ("Data" or "OM") to indicate whether to grab biological parameters from the Data object,
or operating model. Alternatively, a named list to provide custom parameters for the assessment.

- ...
Additional arguments (to be added).

## Data

Currently uses catch, CAA, and indices of abundance in the corresponding slots in the Data object.

## StockPars

Biological parameters can be used from the (1) Data object, (2) operating model, or (3) provided directly in the
`StockPars`

argument.

Options 2 and 3 allow for time-varying growth, maturity, and natural mortality. Natural mortality can also be age-varying.

`StockPars`

can be a named list of parameters used to provide inputs to the assessment model:

`Wt_age`

- annual weight at age, array [sim, ages, year]

`Mat_age`

- annual maturity at age, array [sim, ages, year]

`hs`

- Stock-recruit steepness, vector of length [sim]

`M_ageArray`

- annual natural mortality, array [sim, ages, year]

## Examples

```
r <- RCM_assess(Data = SimulatedData)
myMP <- make_MP(RCM_assess, HCR_MSY)
myMP(x = 1, Data = SimulatedData)
#> TAC (median)
#> 1504.07
```