Robust selection of variables in linear discriminant analysis

Valentin Todorov ()
Additional contact information
Valentin Todorov: Austro Control GmbH

Statistical Methods & Applications, 2007, vol. 15, issue 3, No 8, 395-407

Abstract: Abstract A commonly used procedure for reduction of the number of variables in linear discriminant analysis is the stepwise method for variable selection. Although often criticized, when used carefully, this method can be a useful prelude to a further analysis. The contribution of a variable to the discriminatory power of the model is usually measured by the maximum likelihood ratio criterion, referred to as Wilks’ lambda. It is well known that the Wilks’ lambda statistic is extremely sensitive to the influence of outliers. In this work a robust version of the Wilks’ lambda statistic will be constructed based on the Minimum Covariance Discriminant (MCD) estimator and its reweighed version which has a higher efficiency. Taking advantage of the availability of a fast algorithm for computing the MCD a simulation study will be done to evaluate the performance of this statistic.

Keywords: Linear discriminant analysis; Variable selection; Wilks’ lambda; Minimum covariance discriminant; MCD (search for similar items in EconPapers)
Date: 2007
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://link.springer.com/10.1007/s10260-006-0032-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:stmapp:v:15:y:2007:i:3:d:10.1007_s10260-006-0032-6

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10260/PS2

DOI: 10.1007/s10260-006-0032-6

Access Statistics for this article

Statistical Methods & Applications is currently edited by Tommaso Proietti

More articles in Statistical Methods & Applications from Springer, Società Italiana di Statistica
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().