Linear Discrimination with Adaptive Ridge Classification Rules
This article considers the use of adaptive ridge classification rules for classifying an observation as coming from one of two multivariate normal distributionsN([mu](1),Â [Sigma]) andN([mu](2),Â [Sigma]). In particular, the asymptotic expected error rates for a general class of these rules are obtained and are compared with that of the usual linear discriminant rule.
Volume (Year): 62 (1997)
Issue (Month): 2 (August)
|Contact details of provider:|| Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description|
|Order Information:|| Postal: http://www.elsevier.com/wps/find/supportfaq.cws_home/regional|
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- T. Anderson, 1951. "Classification by multivariate analysis," Psychometrika, Springer, vol. 16(1), pages 31-50, March.
- Loh, W. L., 1995. "On Linear Discriminant Analysis with Adaptive Ridge Classification Rules," Journal of Multivariate Analysis, Elsevier, vol. 53(2), pages 264-278, May.
When requesting a correction, please mention this item's handle: RePEc:eee:jmvana:v:62:y:1997:i:2:p:169-180. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei)
If references are entirely missing, you can add them using this form.