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author | Ricardo Wurmus <rekado@elephly.net> | 2020-02-26 10:12:14 +0100 |
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committer | Ricardo Wurmus <rekado@elephly.net> | 2020-02-26 10:12:14 +0100 |
commit | 762d3ca3dd201e3a0ae15adf128354bf70c918a4 (patch) | |
tree | 2fd851b3c37a865dfaa36a30514eae85090d64ce /gnu/packages | |
parent | 70af390f62262ca52173d908a9ffeb334f0e4589 (diff) | |
download | guix-762d3ca3dd201e3a0ae15adf128354bf70c918a4.tar.gz |
gnu: Add r-loo.
* gnu/packages/cran.scm (r-loo): New variable.
Diffstat (limited to 'gnu/packages')
-rw-r--r-- | gnu/packages/cran.scm | 33 |
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+))) |