A ROBUST METHOD OF ESTIMATING COVARIANCE MATRIX IN MULTIVARIATE DATA ANALYSIS
G.M. Oyeyemi () and
R.A. Ipinyomi ()
Additional contact information
R.A. Ipinyomi: Department of Statistics, University of Ilorin, Nigeria
Analele Stiintifice ale Universitatii "Alexandru Ioan Cuza" din Iasi - Stiinte Economice (1954-2015), 2009, vol. 56, 586-601
We proposed a robust method of estimating covariance matrix in multivariate data set. The goal is to compare the proposed method with the most widely used robust methods (Minimum Volume El-lipsoid and Minimum Covariance Determinant) and the classical method (MLE) in detection of outliers at different levels and magnitude of outliers. The proposed robust method competes favoura-bly well with both MVE and MCD and performed better than any of the two methods in detection of single or fewer outliers especially for small sample size and when the magnitude of outliers is relatively small.
Keywords: Covariance Matrix; Minimum Volume Ellipsoid (MVE); Minimum Covariance De-terminant (MCD); Mahalanobis Distance; Optimality criteria (search for similar items in EconPapers)
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:aic:journl:y:2009:v:56:p:586-601
Access Statistics for this article
More articles in Analele Stiintifice ale Universitatii "Alexandru Ioan Cuza" din Iasi - Stiinte Economice (1954-2015) from Alexandru Ioan Cuza University, Faculty of Economics and Business Administration Contact information at EDIRC.
Bibliographic data for series maintained by Sireteanu Napoleon-Alexandru ().