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authorRicardo Wurmus <rekado@elephly.net>2020-02-26 10:12:14 +0100
committerRicardo Wurmus <rekado@elephly.net>2020-02-26 10:12:14 +0100
commit762d3ca3dd201e3a0ae15adf128354bf70c918a4 (patch)
tree2fd851b3c37a865dfaa36a30514eae85090d64ce /gnu
parent70af390f62262ca52173d908a9ffeb334f0e4589 (diff)
downloadpatches-762d3ca3dd201e3a0ae15adf128354bf70c918a4.tar
patches-762d3ca3dd201e3a0ae15adf128354bf70c918a4.tar.gz
gnu: Add r-loo.
* gnu/packages/cran.scm (r-loo): New variable.
Diffstat (limited to 'gnu')
-rw-r--r--gnu/packages/cran.scm33
1 files changed, 33 insertions, 0 deletions
diff --git a/gnu/packages/cran.scm b/gnu/packages/cran.scm
index 618f892cc9..15a39c9cad 100644
--- a/gnu/packages/cran.scm
+++ b/gnu/packages/cran.scm
@@ -20436,3 +20436,36 @@ up the required package structure, S3 generics and default methods to unify
function naming across Stan-based R packages, and vignettes with
recommendations for developers.")
(license license:gpl3+)))
+
+(define-public r-loo
+ (package
+ (name "r-loo")
+ (version "2.2.0")
+ (source
+ (origin
+ (method url-fetch)
+ (uri (cran-uri "loo" version))
+ (sha256
+ (base32
+ "1hq1zcj76x55z9kic6cwf7mfq9pzqfbr341jbc9wp7x8ac4zcva6"))))
+ (properties `((upstream-name . "loo")))
+ (build-system r-build-system)
+ (inputs
+ `(("pandoc" ,ghc-pandoc)
+ ("pandoc-citeproc" ,ghc-pandoc-citeproc)))
+ (propagated-inputs
+ `(("r-checkmate" ,r-checkmate)
+ ("r-matrixstats" ,r-matrixstats)))
+ (home-page "https://mc-stan.org/loo/")
+ (synopsis "Leave-One-Out cross-validation and WAIC for Bayesian models")
+ (description
+ "This package provides an implementation of efficient approximate
+@dfn{leave-one-out} (LOO) cross-validation for Bayesian models fit using
+Markov chain Monte Carlo, as described in @url{doi:10.1007/s11222-016-9696-4}.
+The approximation uses @dfn{Pareto smoothed importance sampling} (PSIS), a new
+procedure for regularizing importance weights. As a byproduct of the
+calculations, we also obtain approximate standard errors for estimated
+predictive errors and for the comparison of predictive errors between models.
+The package also provides methods for using stacking and other model weighting
+techniques to average Bayesian predictive distributions.")
+ (license license:gpl3+)))