[bug#42117,09/17] gnu: Add r-tidyposterior.
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Message ID 20200629055042.8565-9-peterloleungyau@gmail.com
State New
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  • [bug#42117,01/17] gnu: Add r-hardhat.
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Commit Message

Peter Lo June 29, 2020, 5:50 a.m. UTC
* gnu/packages/cran.scm (r-tidyposterior): New variable.
 gnu/packages/cran.scm | 42 ++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 42 insertions(+)

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diff --git a/gnu/packages/cran.scm b/gnu/packages/cran.scm
index bec5bfb45c..74728ae155 100644
--- a/gnu/packages/cran.scm
+++ b/gnu/packages/cran.scm
@@ -22572,3 +22572,45 @@  functions and classes to be used in conjunction with other
 hyper-parameters in models, pre-processing methods, and
 post-processing steps.")
     (license license:expat)))
+(define-public r-tidyposterior
+  (package
+    (name "r-tidyposterior")
+    (version "0.0.3")
+    (source
+      (origin
+        (method url-fetch)
+        (uri (cran-uri "tidyposterior" version))
+        (sha256
+          (base32
+            "0wsv800w056ziqbnwal7ncmdy4li8cn5yrdx07w35b7j8kl4mwhg"))))
+    (properties `((upstream-name . "tidyposterior")))
+    (build-system r-build-system)
+    (propagated-inputs
+      `(("r-dplyr" ,r-dplyr)
+        ("r-generics" ,r-generics)
+        ("r-ggplot2" ,r-ggplot2)
+        ("r-lifecycle" ,r-lifecycle)
+        ("r-purrr" ,r-purrr)
+        ("r-rlang" ,r-rlang)
+        ("r-rsample" ,r-rsample)
+        ("r-rstanarm" ,r-rstanarm)
+        ("r-tibble" ,r-tibble)
+        ("r-tidyr" ,r-tidyr)
+        ("r-vctrs" ,r-vctrs)))
+    (native-inputs `(("r-knitr" ,r-knitr)))
+    (home-page
+      "https://tidyposterior.tidymodels.org")
+    (synopsis
+      "Bayesian Analysis to Compare Models using Resampling Statistics")
+    (description
+      "Bayesian analysis used here to answer the question: \"when
+looking at resampling results, are the differences between models
+'real'?\" To answer this, a model can be created were the performance
+statistic is the resampling statistics (e.g.  accuracy or RMSE).
+These values are explained by the model types.  In doing this, we can
+get parameter estimates for each model's affect on performance and
+make statistical (and practical) comparisons between models.  The
+methods included here are similar to Benavoli et al (2017)
+    (license license:gpl2)))