A Modified Two-Parameter Estimator in Linear Regression
Ashok V. Dorugade ()
Statistics in Transition new series, 2014, vol. 15, issue 1, 23-36
Abstract:
In this article, a modified two-parameter estimator is introduced for the vector of parameters in the linear regression model when data exists with multicollinearity. The properties of the proposed estimator are discussed and the performance in terms of the matrix mean square error criterion over the ordinary least squares (OLS) estimator, a new two-parameter estimator (NTP), an almost unbiased two-parameter estimator (AUTP) and other well known estimators reviewed in this article is investigated. A numerical example and simulation study are finally conducted to illustrate the superiority of the proposed estimator.
Keywords: Liu estimator; multicollinearity; two-parameter estimator; mean squared error matrix (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://index.stat.gov.pl/repec/files/csb/stintr/csb_stintr_v15_2014_i1_n3.pdf (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:csb:stintr:v:15:y:2014:i:1:p:23-36
Access Statistics for this article
Statistics in Transition new series is currently edited by Włodzimierz Okrasa
More articles in Statistics in Transition new series from Główny Urząd Statystyczny (Polska) Contact information at EDIRC.
Bibliographic data for series maintained by Beata Witek ( this e-mail address is bad, please contact ).