Robust sliced inverse regression
Other Title(s)
الانحدار المعكوس المجزأ الحصين
Source
al-Qadisiya Journal For Administrative and Economic Sciences
Issue
Vol. 16, Issue 1 (31 Mar. 2014), pp.10-25, 16 p.
Publisher
University of al-Qadisiyah College of Administration and Economics
Publication Date
2014-03-31
Country of Publication
Iraq
No. of Pages
16
Main Subjects
Economics & Business Administration (Multidisciplinary)
Abstract EN
In this paper, two methods were suggested to make the estimations of Effective Dimension Reduction directions (E.D.R.-directions) robust in sliced inverse regression (SIR), through the robust estimate of the matrix of covariance, which depends upon the method, by using fast consistent high breakdown (FCH) and reweighted fast consistent high breakdown (RFCH) methods, we called the proposed methods (FCH-SIR) and (RFCH-SIR).
Data has been contaminating by two types of outliers values which are asymmetric contamination (ACN) and symmetric contamination (SCN), and different contaminating ratios and sample sizes.
Have been reached, through simulation experiments and real data.
Conclusions showed that the two proposed methods in this paper gave better results compared to the ordinary SIR depending on the mean square errors (MSE) criterion for comparison.
American Psychological Association (APA)
Dakhil, Tahir Risan. 2014. Robust sliced inverse regression. al-Qadisiya Journal For Administrative and Economic Sciences،Vol. 16, no. 1, pp.10-25.
https://search.emarefa.net/detail/BIM-670254
Modern Language Association (MLA)
Dakhil, Tahir Risan. Robust sliced inverse regression. al-Qadisiya Journal For Administrative and Economic Sciences Vol. 16, no. 1 (2014), pp.10-25.
https://search.emarefa.net/detail/BIM-670254
American Medical Association (AMA)
Dakhil, Tahir Risan. Robust sliced inverse regression. al-Qadisiya Journal For Administrative and Economic Sciences. 2014. Vol. 16, no. 1, pp.10-25.
https://search.emarefa.net/detail/BIM-670254
Data Type
Journal Articles
Language
English
Record ID
BIM-670254