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>.
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Dependency Anatomy Guide
Understanding Dependency Borders
Dependencies are visually distinguished by their border styles to help you understand their relationship to the current package:
Direct Dependencies
Thick solid border: These are dependencies directly specified in the package's DESCRIPTION file (Depends, Imports, Enhances, or LinkingTo).
Recursive Dependencies
Thin solid border: These are dependencies of dependencies (recursive/indirect dependencies). They are initially hidden but can be toggled with the switch button.
Version Constraint Conflicts
Thick border + Info icon: When both direct and recursive dependencies exist for the same package with different version constraints. This indicates the "true" version constraint for the package, as the recursive dependency requires the more strict version constraint.
Understanding the Info Icon
The yellow info circle appears when there are version constraint conflicts between direct and recursive dependencies for the same package. This helps give a more accurate picture of the version constraints for the dependencies of a given package.