effectsize (version 0.3.3)

interpret_ess: Interpret Bayesian diagnostic indices

Description

Interpretation of Bayesian indices, such as Effective Sample Size (ESS), Rhat, or percentage in ROPE.

Usage

interpret_ess(ess, rules = "burkner2017")
interpret_rhat(rhat, rules = "vehtari2019")

Arguments

ess

Value or vector of Effective Sample Size (ESS) values.

rules

A character string (see details) or a custom set of rules().

rhat

Value or vector of Rhat values.

Details

Rules sets:

• ESS: Can be "burkner2017" (default).

• Rhat: Can be "vehtari2019" (default) or "gelman1992".

References

• B<U+00FC>rkner, P. C. (2017). brms: An R package for Bayesian multilevel models using Stan. Journal of Statistical Software, 80(1), 1-28.

• Gelman, A., & Rubin, D. B. (1992). Inference from iterative simulation using multiple sequences. Statistical science, 7(4), 457-472.

• Vehtari, A., Gelman, A., Simpson, D., Carpenter, B., & B<U+00FC>rkner, P. C. (2019). Rank-normalization, folding, and localization: An improved Rhat for assessing convergence of MCMC. arXiv preprint arXiv:1903.08008.

Examples

# NOT RUN {
interpret_ess(1001)
interpret_ess(c(852, 1200))

interpret_rhat(1.00)
interpret_rhat(c(1.5, 0.9))
# }