interpret_ess function

Interpret Bayesian Diagnostic Indices

Interpretation of Bayesian diagnostic indices, such as Effective Sample Size (ESS) and Rhat.

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 Rules) or a custom set of rules().
• rhat: Value or vector of Rhat values.

Rules

ESS

• Bürkner, P. C. (2017) ("burkner2017"; default)

  • ESS \< 1000 - Insufficient
  • ESS \>= 1000 - Sufficient

Rhat

• Vehtari et al. (2019) ("vehtari2019"; default)

  • Rhat \< 1.01 - Converged
  • Rhat \>= 1.01 - Failed

• Gelman & Rubin (1992) ("gelman1992")

  • Rhat \< 1.1 - Converged
  • Rhat \>= 1.1 - Failed

Examples

interpret_ess(1001)
interpret_ess(c(852, 1200))

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

References

• Bürkner, 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., & Bürkner, P. C. (2019). Rank-normalization, folding, and localization: An improved Rhat for assessing convergence of MCMC. arXiv preprint arXiv:1903.08008.