Research Article

Statistical modelling of functional data

  1. Philippe C. Besse1,*,
  2. Hervé Cardot1,2,
  3. Robert Faivre2,
  4. Michel Goulard2

Article first published online: 23 MAR 2005

DOI: 10.1002/asmb.539

Issue

Applied Stochastic Models in Business and Industry

Applied Stochastic Models in Business and Industry

Special Issue: Statistical Learning

Volume 21, Issue 2, pages 165–173, March/April 2005

Additional Information

How to Cite

Besse, P. C., Cardot, H., Faivre, R. and Goulard, M. (2005), Statistical modelling of functional data. Appl. Stochastic Models Bus. Ind., 21: 165–173. doi: 10.1002/asmb.539

Author Information

  1. 1

    Laboratoire de Statistique et Probabilités, UMR CNRS C5583, Université Paul Sabatier, 31062 Toulouse Cedex, France

  2. 2

    INRA Toulouse, Biométrie et Intelligence Artificielle, 31326 Castanet-Tolosan Cedex, France

*Laboratoire de Statistique et Probabilités, UMR CNRS C5583, Université Paul Sabatier, 31062 Toulouse Cedex, France

Publication History

  1. Issue published online: 23 MAR 2005
  2. Article first published online: 23 MAR 2005

SEARCH

SEARCH BY CITATION

ARTICLE TOOLS

Get PDF (125K)

Keywords:

  • functional principal components analysis;
  • ill-posed problems;
  • Karhunen–Loeve expansion;
  • longitudinal data;
  • multilogit model;
  • penalty;
  • regularization;
  • smoothing;
  • SPOT4/Végétation sensor

Abstract

This paper presents some statistical models and estimation procedures when the explanatory variables are functions. We put the stress on the fact that regularization techniques are needed in order to get stable and reliable estimations. Then, an application in remote sensing in presented. It shows the potential of these kind of models to handle real life problems. Copyright © 2005 John Wiley & Sons, Ltd.

Get PDF (125K)