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
Requirements:
· MATLAB Release: R14
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