Package: modi
Type: Package
Title: Multivariate Outlier Detection and Imputation for Incomplete
        Survey Data
Version: 0.1.3
Authors@R: c(
    person("Beat", "Hulliger", email = "beat.hulliger@fhnw.ch", role = c("aut", "cre")),
    person("Martin", "Sterchi", email = "martin.sterchi@fhnw.ch", role = "ctb"),
    person("Tobias", "Schoch", email = "tobias.schoch@fhnw.ch", role = "ctb"))
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
Language: en-GB
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports: MASS (>= 7.3-50), norm (>= 1.0-9.5), stats, graphics, utils
RoxygenNote: 7.3.2
Suggests: knitr, rmarkdown, survey, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-08-22 12:23:29 UTC; hubst
Author: Beat Hulliger [aut, cre],
  Martin Sterchi [ctb],
  Tobias Schoch [ctb]
Maintainer: Beat Hulliger <beat.hulliger@fhnw.ch>
Repository: CRAN
Date/Publication: 2025-08-22 13:10:02 UTC
Built: R 4.6.0; ; 2026-04-27 07:30:15 UTC; unix
