moutlier1

Detection of Outlier in Multivariate Samples Test.

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.