Abstract
Upper and lower bounds for the magnitude of the largest Mahalanobis distance, calculated from n multivariate observations of length p, are derived. These bounds are multivariate extensions of corresponding bounds that arise for the most deviant Z-score calculated from a univariate sample of size n. The approach taken is to pose optimization problems in a mathematical context and to employ variational methods to obtain solutions. The attainability of the bounds obtained is demonstrated. Bounds for related quantities (elements of the "hat matrix") are also derived.
| Original language | English |
|---|---|
| Pages (from-to) | 93-106 |
| Number of pages | 14 |
| Journal | Linear Algebra and Its Applications |
| Volume | 419 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 1 Nov 2006 |
Keywords
- Bound
- Inequality
- Lagrange
- Mahalanobis distance
- Multivariate outlier