Package: RfEmpImp
Type: Package
Title: Multiple Imputation using Chained Random Forests
Version: 2.1.5
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: An R package for methods of multiple imputation using chained
    random forests. Implemented methods can handle missing data in mixed types
    of 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 continuous variables. And the method based on predicted
    probabilities is provided for categorical variables. For node-based
    imputation, the method based on the conditional distribution formed by
    the predicting nodes of random forests, and the method based on proximity
    measures 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 (>= 3.9.0), 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: 2020-06-25 03:23:24 UTC; HONG
Author: Shangzhi Hong [aut, cre],
  Henry S. Lynn [ths]
Repository: CRAN
Date/Publication: 2020-06-25 05:00:02 UTC
Built: R 4.0.2; ; 2020-07-16 22:37:03 UTC; unix
