Detection of Outlier in Multivariate Samples Test.


Updated 23 Oct 2006

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This test is based on the Wilks'method (1963) designed for detection of a single outlier from a normal multivariate sample and approaching the maximun squared Mahalanobis distance to a F distribution function by the Yang and Lee (1987) formulation. A significative squared Mahalanobis distance means an outlier. To test the outlier, this function calls to the zipped ACR m-function.

X - multivariate data matrix.
alpha - significance level (default = 0.05).

- Table of outliers detected in a multivariate sample.

Cite As

Antonio Trujillo-Ortiz (2023). moutlier1 (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R14
Compatible with any release
Platform Compatibility
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