Abstract
By means of a straightforward application of empirical process theory, we show that S-estimators of multivariate location and covariance are asymptotically equivalent to a sum of independent vector and matrix valued random elements respectively. This provides an alternative proof of asymptotic normality of S-estimators and clearly explains the limiting covariance structure. It also leads to a relatively simple proof of asymptotic normality of the length of the shortest alpha-fraction.
Original language | English |
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Pages (from-to) | 220-237 |
Number of pages | 18 |
Journal | Statistica Neerlandica |
Volume | 51 |
Issue number | 2 |
DOIs | |
Publication status | Published - 1997 |
Keywords
- robust estimation of multivariate location and covariance
- asymptotic normality of S-estimators
- application of empirical process theory
- MULTIVARIATE LOCATION
- DISPERSION MATRICES