A New Logistic Ridge Regression Estimator Using Exponentiated Response Function

U.P. Ogoke, E.C. Nduka and M.E. Nja

Journal of Statistical and Econometric Methods, 2013, vol. 2, issue 4, 12

Abstract: The logistic ridge regression estimator was designed to address the problem of variance inflation created by the existence of collinearity among the explanatory variables in logistic regression models. To reduce the bias introduced by the logistic ridge estimator, and at the same time achieve variance reduction, a modified generalized logistic ridge regression estimator is proposed in this paper. By exponentiating the response function, the weight matrix is enhanced, thereby reducing the variance. The modified estimator is jackknifed to achieve bias reduction.

Date: 2013
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.scienpress.com/Upload/JSEM%2fVol%202_4_12.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:spt:stecon:v:2:y:2013:i:4:f:2_4_12

Access Statistics for this article

More articles in Journal of Statistical and Econometric Methods from SCIENPRESS Ltd
Bibliographic data for series maintained by Eleftherios Spyromitros-Xioufis ().