performance
R package 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.
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References in zbMATH (referenced in 6 articles , 1 standard article )
Showing results 1 to 6 of 6.
Sorted by year (- Daniel Lüdecke, Dominique Makowski, Philip Waggoner, Mattan S. Ben-Shachar: see: An R Package for Visualizing Statistical Models (2021) not zbMATH
- Daniel Lüdecke; Mattan S. Ben-Shachar; Indrajeet Patil; Philip Waggoner; Dominique Makowski: performance: An R Package for Assessment, Comparison and Testing of Statistical Models (2021) not zbMATH
- Indrajeet Patil: statsExpressions: R Package for Tidy Dataframes and Expressions with Statistical Details (2021) not zbMATH
- Indrajeet Patil: Visualizations with statistical details: The ggstatsplot approach (2021) not zbMATH
- Daniel Ludecke; Mattan S. Ben-Shachar; Indrajeet Patil; Dominique Makowski: Extracting, Computing and Exploring the Parameters of Statistical Models using R (2020) not zbMATH
- Daniel Lüdecke, Philip D. Waggoner, Dominique Makowski: insight: A Unified Interface to Access Information fromModel Objects in R (2019) not zbMATH