Bayesian analysis used here to answer the question: "when
looking at resampling results, are the differences between models
'real'?" To answer this, a model can be created were the performance
statistic is the resampling statistics (e.g. accuracy or RMSE). These
values are explained by the model types. In doing this, we can get
parameter estimates for each model's affect on performance and make
statistical (and practical) comparisons between models. The methods
included here are similar to Benavoli et al (2017)
<https://jmlr.org/papers/v18/16-305.html>.
| Version: |
1.0.2 |
| Depends: |
R (≥ 4.1) |
| Imports: |
dplyr (> 1.0.0), generics, ggplot2 (≥ 3.5.2), purrr, rlang, rsample (≥ 0.0.2), rstanarm (≥ 2.21.1), stats, tibble, tidyr (≥ 0.7.1), tune (≥ 0.2.0), utils, vctrs (≥ 0.3.0), workflowsets |
| Suggests: |
covr, knitr, parsnip, rmarkdown, splines2, testthat (≥
3.0.0), yardstick |
| Published: |
2025-07-31 |
| DOI: |
10.32614/CRAN.package.tidyposterior |
| Author: |
Max Kuhn  [aut,
cre],
Posit Software, PBC  [cph,
fnd] |
| Maintainer: |
Max Kuhn <max at posit.co> |
| BugReports: |
https://github.com/tidymodels/tidyposterior/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://tidyposterior.tidymodels.org,
https://github.com/tidymodels/tidyposterior |
| NeedsCompilation: |
no |
| Materials: |
NEWS |
| CRAN checks: |
tidyposterior results |