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authorRicardo Wurmus <rekado@elephly.net>2018-10-25 05:16:44 +0200
committerRicardo Wurmus <rekado@elephly.net>2018-10-25 05:17:42 +0200
commitaa4bde0b3a8e012124fabdfd0c74a76abd24597d (patch)
tree3a290aa1a8a45ea47558327ec18804c1bc4d4f9c /gnu
parent3b8a3f554811f675bc68d997476dabd8bf82ae1f (diff)
downloadpatches-aa4bde0b3a8e012124fabdfd0c74a76abd24597d.tar
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gnu: Add r-sjstats.
* gnu/packages/cran.scm (r-sjstats): New variable.
Diffstat (limited to 'gnu')
-rw-r--r--gnu/packages/cran.scm46
1 files changed, 46 insertions, 0 deletions
diff --git a/gnu/packages/cran.scm b/gnu/packages/cran.scm
index 77eb389bdd..70cba10132 100644
--- a/gnu/packages/cran.scm
+++ b/gnu/packages/cran.scm
@@ -6483,3 +6483,49 @@ from R) to obtain an efficient implementation of the applied Laplace
approximation with exact derivatives. Key features are: Automatic sparseness
detection, parallelism through BLAS and parallel user templates.")
(license license:gpl2)))
+
+(define-public r-sjstats
+ (package
+ (name "r-sjstats")
+ (version "0.17.1")
+ (source
+ (origin
+ (method url-fetch)
+ (uri (cran-uri "sjstats" version))
+ (sha256
+ (base32
+ "0s9b0xr8gmcm0kh48jkwk8ns0lqknd8kpys4f7czf0xwzmcx2n1z"))))
+ (build-system r-build-system)
+ (propagated-inputs
+ `(("r-bayesplot" ,r-bayesplot)
+ ("r-broom" ,r-broom)
+ ("r-coin" ,r-coin)
+ ("r-crayon" ,r-crayon)
+ ("r-dplyr" ,r-dplyr)
+ ("r-emmeans" ,r-emmeans)
+ ("r-glmmtmb" ,r-glmmtmb)
+ ("r-lme4" ,r-lme4)
+ ("r-magrittr" ,r-magrittr)
+ ("r-mass" ,r-mass)
+ ("r-matrix" ,r-matrix)
+ ("r-modelr" ,r-modelr)
+ ("r-nlme" ,r-nlme)
+ ("r-purrr" ,r-purrr)
+ ("r-pwr" ,r-pwr)
+ ("r-rlang" ,r-rlang)
+ ("r-sjlabelled" ,r-sjlabelled)
+ ("r-sjmisc" ,r-sjmisc)
+ ("r-tidyr" ,r-tidyr)))
+ (home-page "https://github.com/strengejacke/sjstats")
+ (synopsis "Functions for common statistical computations")
+ (description
+ "This package provides a collection of convenient functions for common
+statistical computations, which are not directly provided by R's @code{base}
+or @code{stats} packages. This package aims at providing, first, shortcuts
+for statistical measures, which otherwise could only be calculated with
+additional effort. Second, these shortcut functions are generic, and can be
+applied not only to vectors, but also to other objects as well. The focus of
+most functions lies on summary statistics or fit measures for regression
+models, including generalized linear models, mixed effects models and Bayesian
+models.")
+ (license license:gpl3)))