moutlier1

Version 1.0.0.0 (4.6 KB) by Antonio Trujillo-Ortiz
Detection of Outlier in Multivariate Samples Test.
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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.

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

Output:
- Table of outliers detected in a multivariate sample.

Cite As

Antonio Trujillo-Ortiz (2024). moutlier1 (https://www.mathworks.com/matlabcentral/fileexchange/12252-moutlier1), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R14
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
1.0.0.0

Text was improved.