MSEtool (version 3.7.3)

Converge: Check Convergence

Description

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

Usage

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
)

Value

A table of convergence results for each MP

Arguments

MSEobj

An MSE object of class 'MSE'

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 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

silent

Hide the messages printed in console?

Author

A. Hordyk

Details

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:

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.

Examples

if (FALSE) {
MSE <- runMSE()
Converge(MSE)
}