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Source: r-cran-rms
Section: gnu-r
Priority: optional
Maintainer: Dirk Eddelbuettel <edd@debian.org>
Build-Depends: debhelper (>= 7.0.0), r-base-dev (>= 3.3.2), cdbs, r-cran-hmisc (>= 4.0-0), r-cran-survival (>= 2.40), r-cran-sparsem, r-cran-quantreg, r-cran-nlme, r-cran-rpart, r-cran-foreign, r-cran-nnet, r-cran-polspline, r-cran-multcomp, r-cran-ggplot2, r-cran-htmltable, r-cran-htmltools
Standards-Version: 3.9.8
Homepage: http://biostat.mc.vanderbilt.edu/wiki/Main/Rrms
Package: r-cran-rms
Architecture: any
Conflicts: r-noncran-design
Replaces: r-noncran-design
Depends: ${shlibs:Depends}, ${misc:Depends}, ${R:Depends}, r-cran-hmisc (>= 4.0-0), r-cran-survival (>= 2.40), r-cran-sparsem, , r-cran-quantreg, r-cran-nlme, r-cran-rpart, r-cran-foreign, r-cran-nnet, r-cran-polspline, r-cran-multcomp, r-cran-ggplot2, r-cran-htmltable, r-cran-htmltools
Description: GNU R regression modeling strategies by Frank Harrell
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.
.
See Frank Harrell (2001), Regression Modeling Strategies, Springer
Series in Statistics, as well as http://biostat.mc.vanderbilt.edu/Rrms.
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