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: |
0.4.0 |
Depends: |
R (≥ 3.0) |
Imports: |
insight (≥ 0.6.0), bayestestR (≥ 0.4.0) |
Suggests: |
AER, betareg, brms, bigutilsr, dbscan, covr, glmmTMB, ICS, ICSOutlier, lavaan, lme4, loo, Matrix, MASS, mlogit, nlme, ordinal, parallel, pscl, psych, randomForest, rmarkdown, rstanarm, rstantools, see (≥ 0.2.1), survival, solitude, testthat |
Published: |
2019-10-21 |
Author: |
Daniel Lüdecke
[aut, cre],
Dominique Makowski
[aut, ctb],
Philip Waggoner
[aut, 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 |
Materials: |
README NEWS |
CRAN checks: |
performance results |