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.

Getting started

Package details

AuthorDaniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>, @strengejacke), Dominique Makowski [aut, ctb] (<https://orcid.org/0000-0001-5375-9967>, @Dom_Makowski), Mattan S. Ben-Shachar [aut, ctb] (<https://orcid.org/0000-0002-4287-4801>, @mattansb), Indrajeet Patil [aut, ctb] (<https://orcid.org/0000-0003-1995-6531>, @patilindrajeets), Philip Waggoner [aut, ctb] (<https://orcid.org/0000-0002-7825-7573>), Brenton M. Wiernik [aut, ctb] (<https://orcid.org/0000-0001-9560-6336>, @bmwiernik), Vincent Arel-Bundock [ctb] (<https://orcid.org/0000-0003-2042-7063>), Martin Jullum [rev], gjo11 [rev]
MaintainerDaniel Lüdecke <d.luedecke@uke.de>
LicenseGPL-3
Version0.8.0
URL https://easystats.github.io/performance/
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("performance")

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performance documentation built on Oct. 1, 2021, 5:08 p.m.