Package: mvoutlier
Version: 2.1.1
Date: 2021-07-29
Title: Multivariate Outlier Detection Based on Robust Methods
Author: Peter Filzmoser <P.Filzmoser@tuwien.ac.at> and
	Moritz Gschwandtner <e0125439@student.tuwien.ac.at>
Maintainer: P. 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: 2021-07-29 17:14:43 UTC; filz
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2021-07-30 08:10:05 UTC
Built: R 4.0.2; ; 2021-07-31 10:35:07 UTC; unix
