Package: tidyposterior 1.0.2.9000

Max Kuhn

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

Authors:Max Kuhn [aut, cre], Posit Software, PBC [cph, fnd]

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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
tidyposterior/json (API)

# Install 'tidyposterior' in R:

install.packages('tidyposterior', repos = c('https://tidymodels.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/tidymodels/tidyposterior/issues

Pkgdown/docs site:https://tidyposterior.tidymodels.org

Datasets:

concrete_example - Example Data Sets
contrast_samples - Example Data Sets
noisy_example - Example Data Sets
posterior_samples - Example Data Sets
precise_example - Example Data Sets
ts_example - Example Data Sets

On CRAN:

8.25 score 103 stars 347 scripts 598 downloads 34 exports 163 dependencies

Last updated from:3f8ee55d5f. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	357
source / vignettes	OK	317
linux-release-x86_64	OK	323
macos-release-arm64	OK	187
macos-oldrel-arm64	OK	149
windows-devel	OK	323
windows-release	OK	269
windows-oldrel	OK	257
wasm-release	OK	184

Exports:autoplot contrast_models Fisher_trans inv_trans ln_trans logit_trans no_trans perf_mod tidy tidy.perf_mod vec_cast.data.frame.posterior vec_cast.data.frame.posterior_diff vec_cast.posterior_diff.data.frame vec_cast.posterior_diff.posterior_diff vec_cast.posterior_diff.tbl_df vec_cast.posterior.data.frame vec_cast.posterior.posterior vec_cast.posterior.tbl_df vec_cast.tbl_df.posterior vec_cast.tbl_df.posterior_diff vec_proxy.posterior vec_proxy.posterior_diff vec_ptype2.data.frame.posterior vec_ptype2.data.frame.posterior_diff vec_ptype2.posterior_diff.data.frame vec_ptype2.posterior_diff.posterior_diff vec_ptype2.posterior_diff.tbl_df vec_ptype2.posterior.data.frame vec_ptype2.posterior.posterior vec_ptype2.posterior.tbl_df vec_ptype2.tbl_df.posterior vec_ptype2.tbl_df.posterior_diff vec_restore.posterior vec_restore.posterior_diff

Dependencies:abind backports base64enc bayesplot BH boot bslib cachem callr checkmate class cli clock codetools colourpicker commonmark cpp11 crosstalk data.table desc diagram dials DiceDesign digest distributional dplyr DT dygraphs evaluate farver fastmap fontawesome fs furrr future future.apply GauPro generics ggplot2 ggridges globals glue gower gridExtra gtable gtools hardhat highr htmltools htmlwidgets httpuv igraph inline ipred isoband jquerylib jsonlite KernSmooth knitr labeling later lattice lava lazyeval lbfgs lifecycle listenv litedown lme4 loo lubridate magrittr markdown MASS Matrix matrixStats memoise mime miniUI minqa mixopt modelenv nlme nloptr nnet numDeriv otel parallelly parsnip pillar pkgbuild pkgconfig plyr posterior prettyunits processx prodlim progressr promises ps purrr QuickJSR R6 rappdirs rbibutils RColorBrewer Rcpp RcppArmadillo RcppEigen RcppParallel Rdpack recipes reformulas reshape2 rlang rmarkdown rpart rsample rstan rstanarm rstantools S7 sass scales sfd shape shiny shinyjs shinystan shinythemes slider sourcetools sparsevctrs splitfngr SQUAREM StanHeaders stringi stringr survival tailor tensorA threejs tibble tidyr tidyselect timechange timeDate tinytex tune tzdb utf8 vctrs viridisLite warp withr workflows workflowsets xfun xtable xts yaml yardstick zoo

Introduction to tidyposterior

Rendered fromtidyposterior.Rmdusingknitr::rmarkdown

Last update: 2022-03-01
Started: 2022-03-01

Help page	Topics
Visualize the Posterior Distributions of Model Statistics	autoplot.perf_mod autoplot.perf_mod_workflow_set autoplot.posterior
Visualize the Posterior Distributions of Model Differences	autoplot.posterior_diff
Estimate the Difference Between Models	contrast_models
Simple Transformation Functions	Fisher_trans inv_trans ln_trans logit_trans no_trans
Bayesian Analysis of Resampling Statistics	perf_mod perf_mod.data.frame perf_mod.resamples perf_mod.rset perf_mod.tune_results perf_mod.workflow_set
Example Data Sets	concrete_example contrast_samples ex_object noisy_example posterior_samples precise_example ts_example
Summarize the Posterior Distributions of Model Statistics	summary.posterior
Summarize Posterior Distributions of Model Differences	summary.posterior_diff
Extract Posterior Distributions for Models	tidy.perf_mod

Package: tidyposterior 1.0.2.9000

tidyposterior: Bayesian Analysis to Compare Models using Resampling Statistics

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