powerbrmsINLA
Bayesian Power Analysis Using 'brms' and 'INLA'
Provides tools for Bayesian power analysis and assurance calculations using the statistical frameworks of 'brms' and 'INLA'. Includes simulation-based approaches, support for multiple decision rules (direction, threshold, ROPE), sequential designs, and visualisation helpers. Methods are based on Kruschke (2014, ISBN:9780124058880) "Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan", O'Hagan & Stevens (2001) <doi:10.1177/0272989X0102100307> "Bayesian Assessment of Sample Size for Clinical Trials of Cost-Effectiveness", Kruschke (2018) <doi:10.1177/2515245918771304> "Rejecting or Accepting Parameter Values in Bayesian Estimation", Rue et al. (2009) <doi:10.1111/j.1467-9868.2008.00700.x> "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations", and Bürkner (2017) <doi:10.18637/jss.v080.i01> "brms: An R Package for Bayesian Multilevel Models using Stan".
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.1.1 |
rolling linux/jammy R-4.5 | powerbrmsINLA_1.1.1.tar.gz |
236.4 KiB |
1.1.1 |
rolling linux/noble R-4.5 | powerbrmsINLA_1.1.1.tar.gz |
236.3 KiB |
1.1.1 |
rolling source/ R- | powerbrmsINLA_1.1.1.tar.gz |
51.7 KiB |
1.1.1 |
latest linux/jammy R-4.5 | powerbrmsINLA_1.1.1.tar.gz |
236.4 KiB |
1.1.1 |
latest linux/noble R-4.5 | powerbrmsINLA_1.1.1.tar.gz |
236.3 KiB |
1.1.1 |
latest source/ R- | powerbrmsINLA_1.1.1.tar.gz |
51.7 KiB |
1.1.1 |
2026-04-26 source/ R- | powerbrmsINLA_1.1.1.tar.gz |
51.7 KiB |
1.1.1 |
2026-04-23 source/ R- | powerbrmsINLA_1.1.1.tar.gz |
51.7 KiB |
1.1.1 |
2026-04-09 windows/windows R-4.5 | powerbrmsINLA_1.1.1.zip |
239.9 KiB |