Package: mvoutlier
Version: 2.1.4
Date: 2026-02-26
Title: Multivariate Outlier Detection Based on Robust Methods
Authors@R: person("Peter", "Filzmoser", role = c("aut","cre"), email = "P.Filzmoser@tuwien.ac.at")
Author: Peter Filzmoser [aut, cre]
Maintainer: Peter Filzmoser <P.Filzmoser@tuwien.ac.at>
Depends: sgeostat, R (>= 3.1)
Imports: robustbase
Description: Various methods for multivariate outlier detection: arw, a
        Mahalanobis-type method with an adaptive outlier cutoff value;
        locout, a method incorporating local neighborhood; pcout, a
        method for high-dimensional data; mvoutlier.CoDa, a method for
        compositional data. References are provided in the
        corresponding help files.
LazyData: TRUE
License: GPL (>= 3)
URL: http://cstat.tuwien.ac.at/filz/
Packaged: 2026-10-14 11:51:52 UTC; root
NeedsCompilation: no
Repository: https://petertuwien.r-universe.dev
Date/Publication: 2026-02-26 07:40:02 UTC
RemoteUrl: https://github.com/cran/mvoutlier
RemoteRef: HEAD
RemoteSha: f2b871a7c9515647e34c15bb7d42176929fd1b12