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Gelman-Rubin statistic

The Gelman-Rubin statistic allows a statement about the convergence of Monte Carlo simulations.

Definition

Monte Carlo simulations (chains) are started with different initial values. The samples from the respective burn-in phases are discarded. From the samples (of the j-th simulation), the variance between the chains and the variance in the chains is estimated:

Mean value of chain j
Mean of the means of all chains
Variance of the means of the chains
Averaged variances of the individual chains across all chains

An estimate of the Gelman-Rubin statistic then results as

.

When L tends to infinity and B tends to zero, R tends to 1.

A different formula is given by Vats & Knudson.

Alternatives

The Geweke Diagnostic compares whether the mean of the first x percent of a chain and the mean of the last y percent of a chain match.

Literature

References