View source: R/MSE_functions.R

Converge | R Documentation |

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

Converge( MSEobj, PMs = c("Yield", "P10", "AAVY"), maxMP = 15, thresh = 0.5, ref.it = 20, inc.leg = FALSE, all.its = FALSE, nrow = NULL, ncol = NULL, silent = FALSE )

`MSEobj` |
An MSE object of class |

`PMs` |
A character vector of names of the PM methods or a list of the PM methods |

`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` |
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 |

`silent` |
Hide the messages printed in console? |

Performance metrics are plotted against the number of simulations. Convergence diagnostics
are calculated over the last `ref.it`

(default = 20) iterations. The convergence diagnostics are:

Is the order of the MPs stable over the last

`ref.it`

iterations?Is the average difference in performance statistic over the last

`ref.it`

iterations <`thresh`

?

By default three commonly used performance metrics are used:

Average Yield Relative to Reference Yield

Probability Spawning Biomass is above 0.1BMSY

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.

A table of convergence results for each MP

A. Hordyk

## Not run: MSE <- runMSE() Converge(MSE) ## End(Not run)

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