Union-Intersection testing for outliers in multivariate normal data
- 1 February 1995
- journal article
- research article
- Published by Taylor & Francis in Journal of Statistical Computation and Simulation
- Vol. 51 (2-4) , 185-196
- https://doi.org/10.1080/00949659508811631
Abstract
The union-intersection approach to multivariate test construction is used to develop an alternative to Wilks' likelihood ratio test statistic for testing for two or more outliers in multivariate normal data. It is shown that critical values of both statistics are poorly approximated by Bonferroni bounds. Simulated critical values are presented for both statistics for significance levels 1% and 5%, for sample sizes 10(5)30, 40, 50, 75 and 100 for 2, 3, 4 and 5 dimensions. A power comparison of the two tests in the slippage of the mean model for generating outliers indicates that the union-intersection test is the more powerful when the slippages are close to collinear. Although Wilks' test remains the preference for general use, the union-intersection test could be valuable when such special structure in the data is suspected.Keywords
This publication has 7 references indexed in Scilit:
- Sequential Application of Wilks's Multivariate Outlier TestJournal of the Royal Statistical Society Series C: Applied Statistics, 1992
- Multivariate outlier tests with structured co variance matricesJournal of Statistical Computation and Simulation, 1991
- Unmasking Multivariate Outliers and Leverage PointsJournal of the American Statistical Association, 1990
- A New Graphical Method for Detecting Single and Multiple Outliers in Univariate and Multivariate DataJournal of the Royal Statistical Society Series C: Applied Statistics, 1987
- Introduction to Multivariate AnalysisPublished by Springer Nature ,1980
- Identification of OutliersPublished by Springer Nature ,1980
- On the exact finite series distribution of the smallest or the largest root of matrices in three situationsJournal of Multivariate Analysis, 1972