Random-effect standard deviations and correlations
Usage
# S3 method for class 'bqmm'
VarCorr(x, sigma = 1, ...)Value
A named numeric vector of posterior-median random-effect standard
deviations (with a posterior-median correlation matrix attached as the
"correlation" attribute for unstructured models), or NULL if the model
has no random effects.
Examples
# \donttest{
fit <- bqmm(distance ~ age + (1 | Subject), data = nlme::Orthodont,
tau = 0.5, chains = 1, iter = 300, refresh = 0, seed = 1)
#> Warning: The largest R-hat is 1.07, indicating chains have not mixed.
#> Running the chains for more iterations may help. See
#> https://mc-stan.org/misc/warnings.html#r-hat
#> Warning: Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable.
#> Running the chains for more iterations may help. See
#> https://mc-stan.org/misc/warnings.html#bulk-ess
#> Warning: Tail Effective Samples Size (ESS) is too low, indicating posterior variances and tail quantiles may be unreliable.
#> Running the chains for more iterations may help. See
#> https://mc-stan.org/misc/warnings.html#tail-ess
#> Warning: Some Rhat > 1.01; chains may not have converged.
#> Warning: Some effective sample sizes < 100; consider more iterations.
VarCorr(fit)
#> Subject : (Intercept)
#> 2.302257
# }