Calculates the Gelman-Rubin criterion for convergence (uses gelman.diag from package coda).

GR_crit(object, confidence = 0.95, transform = FALSE,
  autoburnin = TRUE, multivariate = TRUE, subset = NULL,
  start = NULL, end = NULL, thin = NULL, warn = TRUE,
  mess = TRUE, ...)



object inheriting from class 'JointAI'


the coverage probability of the confidence interval for the potential scale reduction factor


a logical flag indicating whether variables in x should be transformed to improve the normality of the distribution. If set to TRUE, a log transform or logit transform, as appropriate, will be applied.


a logical flag indicating whether only the second half of the series should be used in the computation. If set to TRUE (default) and start(x) is less than end(x)/2 then start of series will be adjusted so that only second half of series is used.


a logical flag indicating whether the multivariate potential scale reduction factor should be calculated for multivariate chains


subset of parameters/variables/nodes (columns in the MCMC sample). Uses the same logic as the argument monitor_params in lm_imp, glm_imp, clm_imp, lme_imp, glme_imp, survreg_imp and coxph_imp.


the first iteration of interest (see window.mcmc)


the last iteration of interest (see window.mcmc)


thinning interval (see window.mcmc)


logical; should warnings be given? Default is TRUE. Note: this applies only to warnings given directly by JointAI.


logical; should messages be given? Default is TRUE. Note: this applies only to messages given directly by JointAI.


currently not used


Gelman, A and Rubin, DB (1992) Inference from iterative simulation using multiple sequences, Statistical Science, 7, 457-511.

Brooks, SP. and Gelman, A. (1998) General methods for monitoring convergence of iterative simulations. Journal of Computational and Graphical Statistics, 7, 434-455.

See also

The vignette Parameter Selection contains some examples how to specify the argument subset.


mod1 <- lm_imp(y~C1 + C2 + M2, data = wideDF, n.iter = 100)
#> This is new software. Please report any bugs to the package maintainer.
#> Potential scale reduction factors: #> #> Point est. Upper C.I. #> (Intercept) 1.00 1.00 #> C1 1.00 1.00 #> C2 1.03 1.04 #> M22 1.02 1.08 #> M23 1.00 1.01 #> M24 1.01 1.03 #> sigma_y 1.00 1.02 #> #> Multivariate psrf #> #> 1.03