:: Volume 22, Issue 1 (9-2011) ::
مجله‌ی بررسی‌ها 2011, 22(1): 33-44 Back to browse issues page
A Review of Minimum Covariance Determinant Estimator and Its Application
Fatemeh Sadat Hosseini Baharanchi *, Masoud Yarmohammadi
Abstract:   (3823 Views)

The main object of this paper is to introduce a method to identify outliers in multivariate data set. The robust method which is reviewed in this paper is Minimum Covariance Determinant (MCD). Then, two important characteristics of the robust estimators, i.e. the breakdown point and the influence function, are defined. We also present the consistency and finite–sample correction factors for the MCD estimator. Finally, it is shown that MCD method is better than a classical method for detecting outliers of a real data set.

Keywords: Minimum Covariance Determinant estimator, outlier identification, robust distances
Full-Text [PDF 487 kb]   (788 Downloads)    
Type of Study: Research | Subject: General
Received: 2010/08/8 | Accepted: 2011/04/19 | Published: 2015/12/30

XML   Persian Abstract   Print

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 22, Issue 1 (9-2011) Back to browse issues page