Create a summary of a fitted model represented by a coevfit object

Create a summary of a fitted model represented by a coevfit object

# S3 method for class 'coevfit'
summary(object, prob = 0.95, robust = FALSE, ...)

Arguments

object: An object of class coevfit.
prob: A value between 0 and 1 indicating the desired probability to be covered by the uncertainty intervals. The default is 0.95.
robust: If FALSE (the default) the mean is used as the measure of central tendency and the standard deviation as the measure of variability. If TRUE, the median and the median absolute deviation are applied instead.
...: Other potential arguments

Value

List of class coevsummary

Details

The convergence diagnostics rhat, ess_bulk, and ess_tail are described in detail in Vehtari et al. (2020).

References

Aki Vehtari, Andrew Gelman, Daniel Simpson, Bob Carpenter, and Paul-Christian Bürkner (2020). Rank-normalization, folding, and localization: An improved R-hat for assessing convergence of MCMC. Bayesian Analysis. 1–28. dpi:10.1214/20-BA1221

Examples

if (FALSE) { # \dontrun{
# fit dynamic coevolutionary model
fit <- coev_fit(
  data = authority$data,
  variables = list(
    political_authority = "ordered_logistic",
    religious_authority = "ordered_logistic"
  ),
  id = "language",
  tree = authority$phylogeny,
  # additional arguments for cmdstanr::sample()
  chains = 4,
  parallel_chains = 4,
  seed = 1
  )

# print summary of model
summary(fit)
} # }