Functional linear discriminant analysis for irregularly sampled curves

Gareth M. James and Trevor J. Hastie

Journal of the Royal Statistical Society Series B, 2001, vol. 63, issue 3, 533-550

Abstract: We introduce a technique for extending the classical method of linear discriminant analysis (LDA) to data sets where the predictor variables are curves or functions. This procedure, which we call functional linear discriminant analysis (FLDA), is particularly useful when only fragments of the curves are observed. All the techniques associated with LDA can be extended for use with FLDA. In particular FLDA can be used to produce classifications on new (test) curves, give an estimate of the discriminant function between classes and provide a one‐ or two‐dimensional pictorial representation of a set of curves. We also extend this procedure to provide generalizations of quadratic and regularized discriminant analysis.

Date: 2001
References: Add references at CitEc
Citations: View citations in EconPapers (51)

Downloads: (external link)
https://doi.org/10.1111/1467-9868.00297

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:bla:jorssb:v:63:y:2001:i:3:p:533-550

Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-9868

Access Statistics for this article

Journal of the Royal Statistical Society Series B is currently edited by P. Fryzlewicz and I. Van Keilegom

More articles in Journal of the Royal Statistical Society Series B from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().