Linear discriminant analysis for interval data

• Type: Article in International Scientific Journal
• Date: 2006

Authors

silva, apd (Author) Other; brito, p (Author) FEP

Journal

Title: Computational Statistics

Vol. 21 No. 2

Pages: 289-308

ISSN: 0943-4062

Publisher: Springer Nature

Indexing

ISI Web of Knowledge - 50 Citations

Scopus - 54 Citations

Scientific classification

FOS: Natural sciences > Mathematics

Other information

Authenticus ID: P-004-PDN

DOI: 10.1007/s00180-006-0264-9

Abstract (EN): This paper compares different approaches to the multivariate analysis of interval data, focusing on discriminant analysis. Three fundamental approaches are considered. The first approach assumes an uniform distribution in each observed interval, derives the corresponding measures of dispersion and association, and appropriately defines linear combinations of interval variables that maximize the usual discriminant criterion. The second approach expands the original data set into the set of all interval description vertices, and proceeds with a classical analysis of the expanded set. Finally, a third approach replaces each interval by a midpoint and range representation. Resulting representations, using intervals or single points, are discussed and distance based allocation rules are proposed. The three approaches are illustrated on a real data set.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 20