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All Journal Zero : Jurnal Sains, Matematika, dan Terapan
Khair, Ananda Ifrajiani
Universitas Sumatera Utara
Agriculture, Biological Sciences & Forestry Chemistry Mathematics Physics

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Minimum Vollume Ellipsoid (MVE) and Minimum Covariance Determinant (MCD) Methods for Estimating Covariance Matrix in Multivariate Data Khair, Ananda Ifrajiani; Sutarman, Sutarman
ZERO: Jurnal Sains, Matematika dan Terapan Vol 8, No 1 (2024): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v8i1.20808

Abstract

Minimum Volume Ellipsoid (MVE) and Minimum Covariance Determinant (MCD) are robust methods used to handle the outlier problem. Outliers are points that appear to deviate significantly from other data sample points that can have a significant effect on the results of the analysis, so a robust method is needed to solve this problem. MVE and MCD have a high breakdown point or level of resistance to outliers, which is 50%, so that it can overcome the influence of extreme outliers. Based on this research, it is known that by using the same data, the MVE and MCD methods produce more robust estimates that were not affected by outliers. The non robust method just found 10 outliers, while the MVE method found that were 276 data points detected as outliers and for the MCD method, the estimation result is with 257 data points detected as outliers.
Co-Authors Sutarman, Sutarman