R Development Page
Contributed R Packages
Below is a list of all packages provided by project Regression Modeling Strategies.
Important note for package binaries: R-Forge provides these binaries only for the most recent version of R, but not for older versions. In order to successfully install the packages provided on R-Forge, you have to switch to the most recent version of R or, alternatively, install from the package sources (.tar.gz).
Packages
| rms | Regression Modeling Strategies | |||||||||
| Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. rms is a collection of 229 functions that assist with and streamline modeling. It also contains functions for binary and ordinal logistic regression models 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 logistic regression, 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. | ||||||||||
| Version: 3.3-0 | Last change: 2011-08-31 04:52:58+02 | Rev.: 107 | ||||||||||
Download:
 (.tar.gz) |
 (.zip) |
Build status: Current | Stable Release: Get rms 8.0-0 from CRAN | ||||||||||
R install command:
install.packages("rms", repos="http://R-Forge.R-project.org") | ||||||||||
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Build status codes
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