Package: VIM
Version: 5.1.1
Date: 2020-03-10
Title: Visualization and Imputation of Missing Values
Authors@R: c(
  person("Matthias", "Templ", email = "matthias.templ@gmail.com", role = c("aut","cre"), comment=c(ORCID="0000-0002-8638-5276")),
  person("Alexander", "Kowarik", email = "alexander.kowarik@statistik.gv.at", role = c("aut"), comment=c(ORCID="0000-0001-8598-4130")),
  person("Andreas", "Alfons", role = c("aut")),
  person("Bernd", "Prantner", role = c("ctb")))
Depends: R (>= 3.5.0),colorspace,grid,data.table(>= 1.9.4)
Imports: car, grDevices, magrittr, robustbase, stats, sp,
        vcd,MASS,nnet,e1071,methods,Rcpp,utils,graphics,laeken,ranger
Suggests: dplyr, testthat
Description: Methods for the visualization of missing and/or imputed values
    are provided, which can be used for exploring the data and the structure of
    the missing and/or imputed values. Depending on this structure of the missing
    values, the corresponding methods may help to identify the mechanism generating
    the missing values and allows to explore the data including missing values.
    In addition, the quality of imputation can be visually explored using various
    univariate, bivariate, multiple and multivariate plot methods (<doi:10.1007/s11634-011-0102-y>). A graphical user
    interface available in the separate package VIMGUI allows an easy handling of
    the implemented plot methods. 
    Fast imputation methods such as k-nearest neighbor imputation (<doi:10.18637/jss.v074.i07>) and 
    (multiple) EM-based imputation using robust methods are provided (<doi:10.1016/j.csda.2011.04.012>).
LazyData: TRUE
ByteCompile: TRUE
License: GPL (>= 2)
URL: https://github.com/statistikat/VIM
Repository: CRAN
LinkingTo: Rcpp
RoxygenNote: 7.0.2
NeedsCompilation: yes
Packaged: 2020-03-10 14:22:57 UTC; matthias
Author: Matthias Templ [aut, cre] (<https://orcid.org/0000-0002-8638-5276>),
  Alexander Kowarik [aut] (<https://orcid.org/0000-0001-8598-4130>),
  Andreas Alfons [aut],
  Bernd Prantner [ctb]
Maintainer: Matthias Templ <matthias.templ@gmail.com>
Date/Publication: 2020-03-10 16:20:02 UTC
Built: R 4.0.0; x86_64-w64-mingw32; 2020-04-10 12:11:34 UTC; windows
Archs: i386, x64
