tidyposterior: Bayesian Analysis to Compare Models using Resampling Statistics

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) <http://jmlr.org/papers/v18/16-305.html>.

Version: 0.0.2
Depends: R (≥ 2.10)
Imports: rsample (≥ 0.0.2), tidyr (≥ 0.7.1), dplyr, rstanarm (≥ 2.15.3), rlang, utils, purrr, tibble, generics, ggplot2
Suggests: knitr, testthat, covr
Published: 2018-11-15
Author: Max Kuhn [aut, cre], RStudio [cph]
Maintainer: Max Kuhn <max at rstudio.com>
BugReports: https://github.com/tidymodels/tidyposterior/issues
License: GPL-2
URL: https://tidymodels.github.io/tidyposterior
NeedsCompilation: no
Materials: NEWS
CRAN checks: tidyposterior results


Reference manual: tidyposterior.pdf
Vignettes: Different Bayesian Models
Getting Started
Package source: tidyposterior_0.0.2.tar.gz
Windows binaries: r-devel: tidyposterior_0.0.2.zip, r-release: tidyposterior_0.0.2.zip, r-oldrel: tidyposterior_0.0.2.zip
OS X binaries: r-release: tidyposterior_0.0.2.tgz, r-oldrel: tidyposterior_0.0.2.tgz
Old sources: tidyposterior archive

Reverse dependencies:

Reverse imports: tidymodels


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