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, ...)

Arguments

object 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

References

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.

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

Examples

mod1 <- lm_imp(y~C1 + C2 + M2, data = wideDF, n.iter = 100)#> This is new software. Please report any bugs to the package maintainer.GR_crit(mod1)#> 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