calc.mult.GR: Calculate Gelman and Rubin diagnostic multiple times for...
In mixstock: functions for mixed stock analysis

Description Usage Arguments Details Value Note Author(s) See Also Examples

Runs Gelman and Rubin diagnostics from CODA multiple times, to get an idea of the variation in convergence statistics

1	calc.mult.GR(data, n=10, tot=20000, burn=1, verbose=FALSE)

`data`	Mixed stock analysis data (a list with elements `sourcesamp` and `mixsamp`
`n`	Number of replicates to run
`tot`	Total number of iterates for each chain
`burn`	Burn-in time for each chain
`verbose`	Produce verbose output?

Runs calc.GR multiple times, produces a summary table of the maximum point estimate and maximum 97.5% estimate (across all variables) for each run with a different random-number seed.

A matrix with each row giving the random-number seed, max. point estimate, max. 97.5% quantile for each run.

The generally accepted criteria for declaring convergence according to Gelman and Rubin is that all of the 97.5% quantiles of the estimates of shrink factors are less than 1.2.

Ben Bolker

calc.GR