Package: performance 0.18.2.16


Daniel Lüdecke
performance: Assessment of Regression Models Performance
Utilities for computing measures to assess model quality, which are not directly provided by R's 'base' or 'stats' packages. These include e.g. measures like r-squared, intraclass correlation coefficient (Nakagawa, Johnson & Schielzeth (2017) <doi:10.1098/rsif.2017.0213>), root mean squared error or functions to check models for overdispersion, singularity or zero-inflation and more. Functions apply to a large variety of regression models, including generalized linear models, mixed effects models and Bayesian models. References: Lüdecke et al. (2021) <doi:10.21105/joss.03139>.
Authors:
performance_0.18.2.16.tar.gz
performance_0.18.2.16.zip(r-4.7-any)performance_0.18.2.16.zip(r-4.6-any)performance_0.18.2.16.zip(r-4.5-any)
performance_0.18.2.16.tgz(r-4.6-any)performance_0.18.2.16.tgz(r-4.5-any)
performance_0.18.2.16.tar.gz(r-4.7-any)performance_0.18.2.16.tar.gz(r-4.6-any)
performance_0.18.2.16.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
performance/json (API)
| # Install 'performance' in R: |
| install.packages('performance', repos = c('https://easystats.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/easystats/performance/issues
Pkgdown/docs site:https://easystats.github.io
aiceasystatshacktoberfestloomachine-learningmixed-modelsmodelsperformancer2statistics
Last updated from:c1660cfadf. Checks:1 ERROR, 8 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | ERROR | 415 | ||
| source / vignettes | OK | 430 | ||
| linux-release | OK | 386 | ||
| macos-release | OK | 324 | ||
| macos-oldrel | OK | 245 | ||
| windows-devel | OK | 442 | ||
| windows-release | OK | 452 | ||
| windows-oldrel | OK | 414 | ||
| wasm-release | OK | 224 |
Exports:as.dagbinned_residualscheck_autocorrelationcheck_clusterstructurecheck_collinearitycheck_concurvitycheck_convergencecheck_dagcheck_distributioncheck_factorstructurecheck_group_variationcheck_heterogeneity_biascheck_heteroscedasticitycheck_heteroskedasticitycheck_homogeneitycheck_itemscalecheck_kmocheck_modelcheck_multimodalcheck_normalitycheck_outlierscheck_overdispersioncheck_predictionscheck_priorscheck_residualscheck_singularitycheck_sphericitycheck_sphericity_bartlettcheck_symmetrycheck_zeroinflationcompare_performancecronbachs_alphadisplayiccinterval_odds_ratioitem_alphaitem_difficultyitem_discriminationitem_intercoritem_omegaitem_reliabilityitem_split_halfitem_totalcorlooicmaemedian_odds_ratiomodel_performancemsemulticollinearityperformanceperformance_accuracyperformance_aicperformance_aiccperformance_cvperformance_dvourperformance_hosmerperformance_iorperformance_loglossperformance_maeperformance_morperformance_mseperformance_pcpperformance_poorperformance_reliabilityperformance_rmseperformance_rocperformance_rseperformance_scoreprint_htmlprint_mdr2r2_bayesr2_coxsnellr2_efronr2_ferrarir2_kullbackr2_loor2_loo_posteriorr2_mcfaddenr2_mckelveyr2_mlmr2_nagelkerker2_nakagawar2_posteriorr2_somersr2_tjurr2_xur2_zeroinflatedrmsesimulate_residualstest_bftest_likelihoodratiotest_lrttest_performancetest_vuongtest_waldvariance_decomposition
Dependencies:bayestestRdatawizardinsight