interpret_ess: Interpret Bayesian Diagnostic Indices

In effectsize: Indices of Effect Size

Interpret Bayesian Diagnostic Indices

Description

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

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 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

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.

Examples

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

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

effectsize documentation built on July 3, 2024, 9:07 a.m.