Description Usage Arguments Details Value Author(s) References
Computes the Heidleberger and Welch convergence diagnostics for the parameters in an MCMC sequence.
1 |
x |
An object of class |
alpha |
Alpha level for the confidence in the sample mean of the retained iterations. |
error |
Accuracy of the posterior estimates for the parameters. |
keep.rares.conv |
Logical. TRUE or FALSE indicating whether the diagnostic of convergence must be carried out also for the rares category. |
Take care when setting keep.rares.conv as TRUE. The chain for this parameter tends to be unstable and could lead to an error.
A matrix whose columns and rows are the Heidleberger and Welch convergence diagnostics (i.e. stationarity test, number of iterations to keep and to drop, Cramer-von-Mises statistic, halfwidth test, mean, and halfwidth) and the monitored parameters, respectively.
Original version by Brian J. Smith, Nicky Best, Kate Cowles in Boa Package. Adapted version by Raquel Iniesta riniesta@pssjd.org
Heidelberger, P. and Welch, P. (1983). Simulation run length control in the presence of an initial transient. Operations Research, 31, 1109-44.
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