calc.mult.GR {mixstock} | R Documentation

## Calculate Gelman and Rubin diagnostic multiple times for mixed stock analyses

### Description

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

### Usage

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

### Arguments

`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?

### Details

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.

### Value

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

### Note

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.

### Author(s)

Ben Bolker

### See Also

calc.GR

### Examples

    data(simex)
    calc.GR(simex,tot=2000)

[Package mixstock version 0.9.2 Index]