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mvoutlier  

Multivariate Outlier Detection Based on Robust Methods
View on CRAN: Click here


Download and install mvoutlier package within the R console
Install from CRAN:
install.packages("mvoutlier")

Install from Github:
library("remotes")
install_github("cran/mvoutlier")

Install by package version:
library("remotes")
install_version("mvoutlier", "2.1.1")



Attach the package and use:
library("mvoutlier")
Maintained by
P. Filzmoser
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2004-11-11
Latest Update: 2021-07-30
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.
How to cite:
P. Filzmoser (2004). mvoutlier: Multivariate Outlier Detection Based on Robust Methods. R package version 2.1.1, https://cran.r-project.org/web/packages/mvoutlier
Previous versions and publish date:
1.0 (2004-11-11 10:19), 1.1 (2005-05-31 12:11), 1.2.1 (2007-04-27 15:57), 1.2 (2007-04-24 14:21), 1.3 (2007-05-16 17:13), 1.4 (2009-01-22 09:54), 1.5 (2010-11-08 12:22), 1.6 (2011-01-14 08:46), 1.7 (2011-02-08 09:48), 1.8 (2011-04-06 12:12), 1.9.1 (2011-06-02 07:36), 1.9.3 (2011-09-06 09:50), 1.9.4 (2011-11-07 15:05), 1.9.7 (2012-04-19 10:15), 1.9.8 (2012-08-31 15:36), 1.9.9 (2013-01-14 15:17), 1.9 (2011-05-30 20:32), 2.0.3 (2013-08-23 18:54), 2.0.4 (2014-02-25 14:44), 2.0.5 (2014-06-23 08:48), 2.0.6 (2015-01-30 13:00), 2.0.8 (2017-01-16 08:13), 2.0.9 (2018-02-08 23:57)
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