CRAN/E | mvoutlier

mvoutlier

Multivariate Outlier Detection Based on Robust Methods

Installation

About

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.

cstat.tuwien.ac.at/filz/

Key Metrics

Version 2.1.1
R ≥ 3.1
Published 2021-07-30 1004 days ago
Needs compilation? no
License GPL (≥ 3)
CRAN checks mvoutlier results

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Maintainer

Maintainer

P. Filzmoser

P.Filzmoser@tuwien.ac.at

Authors

Peter Filzmoser andMoritz Gschwandtner

Material

Reference manual
Package source

In Views

Robust

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

mvoutlier archive

Depends

sgeostat
R ≥ 3.1

Imports

robustbase

Reverse Imports

cellity
GateFinder

Reverse Suggests

fPortfolio
GWmodel
mplot
shotGroups