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A new way for ranking functional data with applications in diagnostic test

Author

Listed:
  • Graciela Estévez-Pérez

    (Universidade da Coruña)

  • Philippe Vieu

    (Université Paul Sabatier)

Abstract

This is a two faces paper. Firstly, it investigates diagnostic tests in situations when the observed variables are functional, that is, diagnostic tests that use functional variables as biomarkers. A procedure based on functional version of ROC analysis is proposed, the main question being linked with a suitable way for ranking the sample of functional data. The second facet of this paper is to present a general new way for ordering functional data in a self-contained way allowing for a wide scope of applications overpassing the former diagnostic test problem. Finite sample analysis highlight how this ranking procedure behaves for diagnostic test.

Suggested Citation

  • Graciela Estévez-Pérez & Philippe Vieu, 2021. "A new way for ranking functional data with applications in diagnostic test," Computational Statistics, Springer, vol. 36(1), pages 127-154, March.
    • Handle: RePEc:spr:compst:v:36:y:2021:i:1:d:10.1007_s00180-020-01020-z
    DOI: 10.1007/s00180-020-01020-z
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    References listed on IDEAS

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    1. Carlo Sguera & Pedro Galeano & Rosa Lillo, 2014. "Spatial depth-based classification for functional data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(4), pages 725-750, December.
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