gelman.plot: Gelman-Rubin-Brooks plot
In coda: Output Analysis and Diagnostics for MCMC

Description Usage Arguments Details Theory References See Also

This plot shows the evolution of Gelman and Rubin's shrink factor as the number of iterations increases.

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gelman.plot(x, bin.width = 10, max.bins = 50,
confidence = 0.95, transform = FALSE, autoburnin=TRUE, auto.layout = TRUE,
ask, col, lty, xlab, ylab, type, ...)

`x`	an mcmc object
`bin.width`	Number of observations per segment, excluding the first segment which always has at least 50 iterations.
`max.bins`	Maximum number of bins, excluding the last one.
`confidence`	Coverage probability of confidence interval.
`transform`	Automatic variable transformation (see `gelman.diag`)
`autoburnin`	Remove first half of sequence (see `gelman.diag`)
`auto.layout`	If `TRUE` then, set up own layout for plots, otherwise use existing one.
`ask`	Prompt user before displaying each page of plots. Default is `dev.interactive()` in R and `interactive()` in S-PLUS.
`col`	graphical parameter (see `par`)
`lty`	graphical parameter (see `par`)
`xlab`	graphical parameter (see `par`)
`ylab`	graphical parameter (see `par`)
`type`	graphical parameter (see `par`)
`...`	further graphical parameters.

The Markov chain is divided into bins according to the arguments bin.width and max.bins. Then the Gelman-Rubin shrink factor is repeatedly calculated. The first shrink factor is calculated with observations 1:50, the second with observations 1:(50+bin.width), the third contains samples 1:(50+2*bin.width) and so on. If the chain has less than 50 + bin.width iterations then gelman.diag will exit with an error.

A potential problem with gelman.diag is that it may mis-diagnose convergence if the shrink factor happens to be close to 1 by chance. By calculating the shrink factor at several points in time, gelman.plot shows if the shrink factor has really converged, or whether it is still fluctuating.

Brooks, S P. and Gelman, A. (1998) General Methods for Monitoring Convergence of Iterative Simulations. Journal of Computational and Graphical Statistics, 7, 434-455.

gelman.diag.

coda documentation built on Oct. 24, 2020, 9:10 a.m.