Efficient Sequential Testing with Evidence Ratios
Overview
An implementation of sequential testing that uses evidence ratios computed from the weights of a set of models. These weights correspond either to Akaike weights computed from the Akaike Information Criterion (AIC) or the Bayesian Information Criterion (BIC) and following Burnham & Anderson (2004, doi:10.1177/0049124104268644) recommendations, or to pseudo-BMA weights computed from the WAIC or the LOO-IC of models fitted with 'brms' and following Yao et al. (2017, arXiv:1704.02030v3).
Major updates
- deprecating distER.R (will be removed in the next release)
- merging seqER.R and seqERboot.R into seqER.R, by adding a "nsims" argument in seqER.R
- deprecating seqERboot.R (will be removed in the next release)
- simER.R: parallelisation and update of the plot method
- introducing the analysER.R function which allow to analyse the results of simulations ran with simER.R
Minor updates
- doc updates
- adding pseudo-BMA weights computations for brmsfit models in ictab.R
- seqER.R now accepts brmsfit models
- adding a "blind" argument to seqER.R to conduct triple blind analyses, with a "boundary" argument at which the sequential testing is stopped
From NEWS.md in the release
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- Help pages
- 10includes a package overview page
- Examples that run
- 38%3 run in a plain check · 5 never run
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 38%
- Help pages citing references
- 30%
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People & History
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- RR 4.6.0 released · 2026-04-24
- archivedRemoved from CRAN2026-01-18the maintainer's request
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- RR 3.5.0 released · 2018-04-23
- 0.2.0
- 0.1.02017-10-16
- RR 3.4.0 released · 2017-04-21
Package metadata
- First published
- 2017-10-16
- Total releases
- 2 / 9 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 3.3.0
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