Linear discrimination with equicorrelated training vectors
AbstractFisher's linear discrimination rule requires uncorrelated training vectors. In this paper a linear discrimination method is developed to be used when the training vectors are equicorrelated. Also, maximum likelihood ratio tests are proposed to decide whether the training samples are uncorrelated or equicorrelated.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Elsevier in its journal Journal of Multivariate Analysis.
Volume (Year): 98 (2007)
Issue (Month): 2 (February)
Contact details of provider:
Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
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.:
- Paranjpe, S. A. & Gore, A. P., 1994. "Selecting variables for discrimination when covariance matrices are unequal," Statistics & Probability Letters, Elsevier, vol. 21(5), pages 417-419, December.
- Kihoon Yoon & Daijin Ko & Carolina B. Livi & Nathan Trinklein & Mark Doderer & Stephen Kwek & Luiz O. F. Penalva, . "Over-represented sequences located on UTRs are potentially involved in regulatory functions," Working Papers 0053, College of Business, University of Texas at San Antonio.
- Pamela C. Smith & Dana A. Forgione, . "Global Outsourcing of Healthcare: A Medical Tourism Decision Model," Working Papers 0033, College of Business, University of Texas at San Antonio.
- Roy, Anuradha & Leiva, Ricardo, 2008. "Likelihood ratio tests for triply multivariate data with structured correlation on spatial repeated measurements," Statistics & Probability Letters, Elsevier, vol. 78(13), pages 1971-1980, September.
- Leiva, Ricardo & Roy, Anuradha, 2012. "Linear discrimination for three-level multivariate data with a separable additive mean vector and a doubly exchangeable covariance structure," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1644-1661.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.