@@ 1313,3 1313,39 @@ Jaro-Winkler). An implementation of soundex is provided as well. Distances
can be computed between character vectors while taking proper care of encoding
or between integer vectors representing generic sequences.")
(license license:gpl3+)))
+
+(define-public r-mice
+ (package
+ (name "r-mice")
+ (version "2.46.0")
+ (source
+ (origin
+ (method url-fetch)
+ (uri (cran-uri "mice" version))
+ (sha256
+ (base32
+ "1gjvlk67zvgipfczsca8zqk97vg3sivv82hblsdwp14s7smhjcax"))))
+ (build-system r-build-system)
+ (propagated-inputs
+ `(("r-lattice" ,r-lattice)
+ ("r-mass" ,r-mass)
+ ("r-nnet" ,r-nnet)
+ ("r-rcpp" ,r-rcpp)
+ ("r-rpart" ,r-rpart)
+ ("r-survival" ,r-survival)))
+ (home-page "https://cran.r-project.org/web/packages/mice/")
+ (synopsis "Multivariate imputation by chained equations")
+ (description
+ "Multiple imputation using @dfn{Fully Conditional Specification} (FCS)
+implemented by the MICE algorithm as described in @url{Van Buuren and
+Groothuis-Oudshoorn (2011), http://doi.org/10.18637/jss.v045.i03}. Each
+variable has its own imputation model. Built-in imputation models are
+provided for continuous data (predictive mean matching, normal), binary
+data (logistic regression), unordered categorical data (polytomous logistic
+regression) and ordered categorical data (proportional odds). MICE can also
+impute continuous two-level data (normal model, pan, second-level variables).
+Passive imputation can be used to maintain consistency between variables.
+Various diagnostic plots are available to inspect the quality of the
+imputations.")
+ ;; Any of these two versions.
+ (license (list license:gpl2 license:gpl3))))