Converge: Check Convergence In DLMtool: Data-Limited Methods Toolkit

Description

Have I undertaken enough simulations (nsim)? Has my MSE converged on stable (reliable) peformance metrics?

Usage

 ```1 2 3``` ```Converge(MSEobj, PMs = list(Yield, P10, AAVY), maxMP = 15, thresh = 0.5, ref.it = 20, inc.leg = FALSE, all.its = FALSE, nrow = NULL, ncol = NULL) ```

Arguments

 `MSEobj` An MSE object of class `'MSE'` `PMs` A list of PM objects `maxMP` Maximum number of MPs to include in a single plot `thresh` The convergence threshold. Maximum root mean square deviation over the last `ref.it` iterations `ref.it` The number of iterations to calculate the convergence statistics. For example, a value of 20 means convergence diagnostics are calculated over last 20 simulations `inc.leg` Logical. Should the legend be displayed? `all.its` Logical. Plot all iterations? Otherwise only (nsim-ref.it):nsim `nrow` Numeric. Optional. Number of rows `ncol` Numeric. Optional. Number of columns

Details

Performance metrics are plotted against the number of simulations. Convergence diagonostics are calculated over the last `ref.it` (default = 20) iterations. The convergence diagnostics are:

1. Is the order of the MPs stable over the last `ref.it` iterations?

2. Is the average difference in performance statistic over the last `ref.it` iterations < `thresh`?

By default three commonly used performance metrics are used:

1. Average Yield Relative to Reference Yield

2. Probability Spawning Biomass is above 0.1BMSY

3. Probability Average Annual Variability in Yield is < 20 per cent

Additional or alternative performance metrics objects can be supplied. Advanced users can develop their own performance metrics.

Note

 ```1 2 3 4 5``` ```## Not run: MSE <- runMSE() Converge(MSE) ## End(Not run) ```