Gelman-Rubin-Brooks plot

Usage

gelman.plot(mcmc.list.obj, bin.width = 10, max.bins = 50,
confidence = 0.95, transform = FALSE, auto.layout = TRUE, ask = TRUE,
...)

Description

This plot shows what happens to Gelman and Rubin's shrink factor when successively larger numbers of iterations are discarded from the end of the chain (NB This is diferent from geweke.plot).

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+n) where n is the bin width, the third contains samples 1:(50+2n) and so on.

Note

The graphical implementation of Gelman and Rubin's diagnostic was suggested by Steve Brooks.

See Also

gelman.diag, geweke.plot.


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