Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. 'rms' is a collection of functions that assist with and streamline modeling. It also contains functions for binary and ordinal logistic regression models, ordinal models for continuous Y with a variety of distribution families, and the Buckley-James multiple regression model for right-censored responses, and implements penalized maximum likelihood estimation for logistic and ordinary linear models. 'rms' works with almost any regression model, but it was especially written to work with binary or ordinal regression models, Cox regression, accelerated failure time models, ordinary linear models, the Buckley-James model, generalized least squares for serially or spatially correlated observations, generalized linear models, and quantile regression.
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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.