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Semiparametric Models with Functional Responses in a Model Assisted Survey Sampling Setting : Model Assisted Estimation of Electricity Consumption Curves

In: Proceedings of COMPSTAT'2010

Author

Listed:
  • Hervé Cardot

    (Institut de Mathématiques de Bourgogne, UMR 5584 CNRS, Université de Bourgogne)

  • Alain Dessertaine

    (EDF, R&D, ICAME - SOAD)

  • Etienne Josserand

    (Institut de Mathématiques de Bourgogne, UMR 5584 CNRS, Université de Bourgogne)

Abstract

This work adopts a survey sampling point of view to estimate the mean curve of large databases of functional data. When storage capacities are limited, selecting, with survey techniques a small fraction of the observations is an interesting alternative to signal compression techniques. We propose here to take account of real or multivariate auxiliary information available at a low cost for the whole population, with semiparametric model assisted approaches, in order to improve the accuracy of Horvitz-Thompson estimators of the mean curve. We first estimate the functional principal components with a design based point of view in order to reduce the dimension of the signals and then propose semiparametric models to get estimations of the curves that are not observed. This technique is shown to be really effective on a real dataset of 18902 electricity meters measuring every half an hour electricity consumption during two weeks.

Suggested Citation

  • Hervé Cardot & Alain Dessertaine & Etienne Josserand, 2010. "Semiparametric Models with Functional Responses in a Model Assisted Survey Sampling Setting : Model Assisted Estimation of Electricity Consumption Curves," Springer Books, in: Yves Lechevallier & Gilbert Saporta (ed.), Proceedings of COMPSTAT'2010, pages 413-420, Springer.
    • Handle: RePEc:spr:sprchp:978-3-7908-2604-3_39
    DOI: 10.1007/978-3-7908-2604-3_39
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