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| author | Ricardo Wurmus <rekado@elephly.net> | 2019-03-25 09:39:01 +0100 |
|---|---|---|
| committer | Ricardo Wurmus <rekado@elephly.net> | 2019-03-25 10:02:03 +0100 |
| commit | a8c965cfeca16e6a836542a161a6cf8b3eb0bcb5 (patch) | |
| tree | 192e4799771f37cacb50c4f7ece7d7672463f493 | |
| parent | 6a472af3f630aa0ea6e044c72afbe54314d25c55 (diff) | |
| download | patches-a8c965cfeca16e6a836542a161a6cf8b3eb0bcb5.tar patches-a8c965cfeca16e6a836542a161a6cf8b3eb0bcb5.tar.gz | |
gnu: Add r-rms.
* gnu/packages/cran.scm (r-rms): New variable.
| -rw-r--r-- | gnu/packages/cran.scm | 44 |
1 files changed, 44 insertions, 0 deletions
diff --git a/gnu/packages/cran.scm b/gnu/packages/cran.scm index 7ea30dcc74..b69a4defd6 100644 --- a/gnu/packages/cran.scm +++ b/gnu/packages/cran.scm @@ -12434,3 +12434,47 @@ either PDF/EPS files.") routines hazard regression, hazard estimation with flexible tails, logspline, lspec, polyclass, and polymars.") (license license:gpl2+))) + +(define-public r-rms + (package + (name "r-rms") + (version "5.1-3") + (source + (origin + (method url-fetch) + (uri (cran-uri "rms" version)) + (sha256 + (base32 + "1sw9a0iqiips580jpbk7yiqgyiswihvaqbnq4ybsmd4ki86i5isz")))) + (build-system r-build-system) + (propagated-inputs + `(("r-ggplot2" ,r-ggplot2) + ("r-hmisc" ,r-hmisc) + ("r-htmltable" ,r-htmltable) + ("r-htmltools" ,r-htmltools) + ("r-lattice" ,r-lattice) + ("r-multcomp" ,r-multcomp) + ("r-nlme" ,r-nlme) + ("r-polspline" ,r-polspline) + ("r-quantreg" ,r-quantreg) + ("r-rpart" ,r-rpart) + ("r-sparsem" ,r-sparsem) + ("r-survival" ,r-survival))) + (native-inputs `(("gfortran" ,gfortran))) + (home-page "http://biostat.mc.vanderbilt.edu/rms") + (synopsis "Regression modeling strategies") + (description + "This is a package for regression modeling, testing, estimation, +validation, graphics, prediction, and typesetting by storing enhanced model +design attributes in the fit. The rms package 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. The +package 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.") + (license license:gpl2+))) |