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Details for article 19 of 20 found articles
| Title: |
Wilks' outlier test in more than one multivariate sample |
| Author: |
Caroni, C. |
| Appeared in: |
Communications in statistics |
| Paging: | Volume 27 (1998) nr. 1 pages 79-94 |
| Year: |
1998 |
| Contents: |
Wilks' test for a single outlier in a multivariate normal sample is extended to the case of samples from different subpopulations with common covariance matrix, a situation arising in MANOVA, for example. Simulation results show that the size of the test is acceptably robust to moderate heterogeneity in covariances (25-50% difference in total variation), especially if sample sizes are small (below 20 per group). However covariance heterogeneity leads to a drastic loss of power, unless this heterogeneity is concentrated in one dimension and the outlier appears in a different dimension. It is concluded that the extended test should be used with caution since it will often be difficult to establish whether these conditions hold. |
| Publisher: |
Taylor & Francis |
| Source file: |
Elektronische Wetenschappelijke Tijdschriften |
Details for article 19 of 20 found articles
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