Jackknife after bootstrap robust regression
Joint Authors
Rashid, Badl Khayri
Rashid, Safwan Nazim
al-Jamal, Zakariyya Yahya
Source
Journal of Statistical Sciences
Issue
Vol. 2011, Issue 4 (31 Dec. 2011), pp.1-9, 9 p.
Publisher
Arab Institute for Training and Research in Statistics
Publication Date
2011-12-31
Country of Publication
Jordan
No. of Pages
9
Main Subjects
Abstract EN
The least squares method has been in use in regression analysis mainly because of tradition and ease of computation, but this method may suffer a huge setback in the presence of unusual observation such as outliers and high leverage point.
In this paper our main objective was to use jackknife after bootstrap procedure in most of robust regression method like, M-estimator and MM-estimator.
Analytical examples are presented to show the effective of the deleted observation on the coefficients, and the behavior of jackknife after bootstrap in robust regression.
American Psychological Association (APA)
Rashid, Badl Khayri& al-Jamal, Zakariyya Yahya& Rashid, Safwan Nazim. 2011. Jackknife after bootstrap robust regression. Journal of Statistical Sciences،Vol. 2011, no. 4, pp.1-9.
https://search.emarefa.net/detail/BIM-720245
Modern Language Association (MLA)
Rashid, Badl Khayri…[et al.]. Jackknife after bootstrap robust regression. Journal of Statistical Sciences No. 4 (Dec. 2011), pp.1-9.
https://search.emarefa.net/detail/BIM-720245
American Medical Association (AMA)
Rashid, Badl Khayri& al-Jamal, Zakariyya Yahya& Rashid, Safwan Nazim. Jackknife after bootstrap robust regression. Journal of Statistical Sciences. 2011. Vol. 2011, no. 4, pp.1-9.
https://search.emarefa.net/detail/BIM-720245
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p.8-9
Record ID
BIM-720245
