Package: modi
Type: Package
Title: Multivariate Outlier Detection and Imputation for Incomplete
        Survey Data
Version: 0.1.0
Authors@R: c(
    person("Beat", "Hulliger", email = "beat.hulliger@fhnw.ch", role = "aut"),
    person("Martin", "Sterchi", email = "martin.sterchi@fhnw.ch", role = "cre"))
Description: Algorithms for multivariate outlier detection when missing values occur.
    Algorithms are based on Mahalanobis distance or data depth. Imputation is based
    on the multivariate normal model or uses nearest neighbour donors. The algorithms 
    take sample designs, in particular weighting, into account. The methods are 
    described in Bill and Hulliger (2016) <doi:10.17713/ajs.v45i1.86>.
License: MIT + file LICENSE
URL: https://github.com/martinSter/modi
BugReports: https://github.com/martinSter/modi/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports: MASS (>= 7.3-50), norm (>= 1.0-9.5), stats, graphics, utils
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-11-14 08:29:00 UTC; martin.sterchi
Author: Beat Hulliger [aut],
  Martin Sterchi [cre]
Maintainer: Martin Sterchi <martin.sterchi@fhnw.ch>
Repository: CRAN
Date/Publication: 2018-11-20 13:10:07 UTC
Built: R 4.0.5; ; 2022-04-21 03:01:20 UTC; windows
