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.

Version: 0.7.1
Depends: R (≥ 3.4)
Imports: bayestestR (≥ 0.8.2), insight (≥ 0.13.2), stats, utils
Suggests: AER, BayesFactor, betareg, bigutilsr, brms, car, CompQuadForm, correlation, cplm, dbscan, fixest, forecast, gamm4, ggplot2, glmmTMB, gridExtra, ICS, ICSOutlier, ISLR, lavaan, lme4, lmtest, loo, magrittr, MASS, Matrix, metafor, mgcv, mlogit, nlme, nonnest2, ordinal, parallel, parameters, pscl, psych, randomForest, rmarkdown, rstanarm, rstantools, sandwich, see, spelling, survey, survival, testthat, tweedie, VGAM
Published: 2021-04-09
Author: Daniel Lüdecke ORCID iD [aut, cre], Dominique Makowski ORCID iD [aut, ctb], Mattan S. Ben-Shachar ORCID iD [aut, ctb], Indrajeet Patil ORCID iD [aut, ctb], Philip Waggoner ORCID iD [aut, ctb], Vincent Arel-Bundock ORCID iD [ctb]
Maintainer: Daniel Lüdecke <d.luedecke at uke.de>
BugReports: https://github.com/easystats/performance/issues
License: GPL-3
URL: https://easystats.github.io/performance/
NeedsCompilation: no
Language: en-US
Citation: performance citation info
Materials: README NEWS
CRAN checks: performance results

Downloads:

Reference manual: performance.pdf
Package source: performance_0.7.1.tar.gz
Windows binaries: r-devel: performance_0.7.1.zip, r-release: performance_0.7.1.zip, r-oldrel: performance_0.7.1.zip
macOS binaries: r-release: performance_0.7.1.tgz, r-oldrel: performance_0.7.1.tgz
Old sources: performance archive

Reverse dependencies:

Reverse imports: broomExtra, bruceR, drhur, ggstatsplot, modelsummary, report, sjPlot, sjstats, statsExpressions, tidyBF
Reverse suggests: archetyper, bayestestR, dominanceanalysis, effectsize, insight, parameters, pubh, see, specr

Linking:

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