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mvoutlier

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.

Versions across snapshots

VersionRepositoryFileSize
2.1.4 rolling linux/jammy R-4.5 mvoutlier_2.1.4.tar.gz 781.3 KiB
2.1.4 rolling linux/noble R-4.5 mvoutlier_2.1.4.tar.gz 780.9 KiB
2.1.4 rolling source/ R- mvoutlier_2.1.4.tar.gz 466.3 KiB
2.1.4 latest linux/jammy R-4.5 mvoutlier_2.1.4.tar.gz 781.3 KiB
2.1.4 latest linux/noble R-4.5 mvoutlier_2.1.4.tar.gz 780.9 KiB
2.1.4 latest source/ R- mvoutlier_2.1.4.tar.gz 466.3 KiB
2.1.4 2026-04-26 source/ R- mvoutlier_2.1.4.tar.gz 466.3 KiB
2.1.4 2026-04-23 source/ R- mvoutlier_2.1.4.tar.gz 466.3 KiB
2.1.4 2026-04-09 windows/windows R-4.5 mvoutlier_2.1.4.zip 783.2 KiB
2.1.1 2025-04-20 source/ R- mvoutlier_2.1.1.tar.gz 464.7 KiB

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