Package: RfEmpImp
Type: Package
Title: Multiple Imputation using Chained Random Forests
Version: 2.0.3
Authors@R: c(person("Shangzhi", "Hong", role = c("aut", "cre"),
            email = "shangzhi-hong@hotmail.com"),
            person("Henry S.", "Lynn", role = c("ths")))
Maintainer: Shangzhi Hong <shangzhi-hong@hotmail.com>
Description: Functions for methods for multiple imputation using chained random
    forests. Implemented algorithms can handle missing data in both continuous
    and categorical variables by using prediction-based or node-based
    conditional distributions constructed using random forests. For
    prediction-based imputation, the method based on the empirical distribution
    of out-of-bag prediction errors of random forests and the method based on
    normality assumption are provided. For node-based imputation, the method
    based on the conditional distribution formed by predicting nodes of random
    forests and the method based on measures of proximities of random forests
    are provided. More details of the statistical methods can be found in
    Hong et al. (2020) <arXiv:2004.14823>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Depends: R (>= 3.5.0), mice (>= 3.8.0), ranger (>= 0.12.1)
Suggests: testthat (>= 2.1.0), knitr, rmarkdown
NeedsCompilation: no
URL: https://github.com/shangzhi-hong/RfEmpImp
BugReports: https://github.com/shangzhi-hong/RfEmpImp/issues
VignetteBuilder: knitr
Packaged: 2020-05-12 11:49:23 UTC; HONG
Author: Shangzhi Hong [aut, cre],
  Henry S. Lynn [ths]
Repository: CRAN
Date/Publication: 2020-05-16 09:30:11 UTC
