Multivariate Outlier Detection Based on Robust Methods

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.


Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("mvoutlier")

2.1.4 by Peter Filzmoser, 8 months ago


http://cstat.tuwien.ac.at/filz/


Browse source code at https://github.com/cran/mvoutlier


Authors: Peter Filzmoser [aut, cre]


Documentation:   PDF Manual  


GPL (>= 3) license


Imports robustbase

Depends on sgeostat


Imported by DFA.CANCOR, qrfactor.

Suggested by ChemoSpecUtils, GWmodel, fPortfolio, mplot, shotGroups.

Enhanced by cluster.


See at CRAN