Gini-PLS Regressions

Stéphane Mussard and Fattouma Souissi-Benrejab

Working Papers from LAMETA, Universtiy of Montpellier

Abstract: Data contamination and excessive correlations between regressors (multicollinearity) constitute a standard and major problem in econometrics. Two techniques enable solving these problems, in separate ways: the Gini regression for the former, and the PLS (partial least squares) regression for the latter. Gini-PLS regressions are proposed in order to treat extreme values and multicollinearity simultaneously.

Pages: 30 pages
Date: 2015-02, Revised 2015-02
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.lameta.univ-montp1.fr/Documents/DR2015-03.pdf Revised version, 2015 (application/pdf)
Our link check indicates that this URL is bad, the error code is: 500 Can't connect to www.lameta.univ-montp1.fr:80 (No such host is known. )

Related works:
Journal Article: Gini-PLS Regressions (2019)
Working Paper: Gini-PLS Regressions (2017)
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:lam:wpaper:15-03

Access Statistics for this paper

More papers in Working Papers from LAMETA, Universtiy of Montpellier Contact information at EDIRC.
Bibliographic data for series maintained by Patricia Modat ( this e-mail address is bad, please contact ).