A unified description of classical classification methods for multicollinear data

✍ Scribed by Tormod Næs; Ulf Indahl

• Publisher: John Wiley and Sons
• Year: 1998
• Tongue: English
• Weight: 217 KB
• Volume: 12
• Category: Article
• ISSN: 0886-9383
• DOI: 10.1002/(sici)1099-128x(199805/06)12:3<205::aid-cem509>3.0.co;2-n

✦ Synopsis

In this paper a unified description of classification methods in situations with multicollinear data is proposed. It is shown that a number of the well-established methods can be derived by substituting different modified versions of the covariance matrix into either the classical Bayes method or Fisher's linear (canonical) discriminant method. A parametric version of this modified covariance matrix is proposed. Each method corresponds to a particular value of the parameters.