Journal article
The complexity of computing the MCD-estimator
In
Theoretical Computer Science
—
2004, Volume 326, Issue 1-3, pp. 383-398
Abstract
In modem statistics the robust estimation of parameters is a central problem, i.e., an estimation that is not or only slightly affected by outliers in the data. The minimum covariance determinant (MCD) estimator (J. Amer. Statist. Assoc. 79 (1984) 871) is probably one of the most important robust estimators of location and scatter.
The complexity of computing the MCD, however, was unknown and generally thought to be exponential even if the dimensionality of the data is fixed. Here we present a polynomial time algorithm for MCD for fixed dimension of the data. In contrast we show that computing the MCD-estimator is NP-hard if the dimension varies. (C) 2004 Elsevier B.V.
All rights reserved.
| Language: | English |
|---|---|
| Year: | 2004 |
| Pages: | 383-398 |
| ISSN: | 18792294 and 03043975 |
| Types: | Journal article |
| DOI: | 10.1016/j.tcs.2004.08.005 |
| ORCIDs: | Fischer, Paul |
