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Influence in the Functional Linear Model with Scalar Response

  • Manuel Febrero
  • Pedro Galeano
  • Wenceslao González-Manteiga
Conference paper
Part of the Contributions to Statistics book series (CONTRIB.STAT.)

This paper studies how to identify influential curves in the functional linear model in which the response is scalar and the predictor is functional and how to measure their effects on the estimation of the model and on the forecasts, when the model is estimated by the principal components method. For that, we introduce and analyze two statistics that measure the influence of each curve on the functional slope estimate of the model, which are generalizations of the measures proposed for the standard regression model by Cook (1977) and Peña (2005), respectively.

Keywords

Scalar Response Functional Data Analysis Functional Principal Component Analysis Principal Component Method Functional Principal Component 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Physica-Verlag Heidelberg 2008

Authors and Affiliations

  • Manuel Febrero
    • 1
  • Pedro Galeano
    • 1
  • Wenceslao González-Manteiga
    • 1
  1. 1.Departamento de Estadística e Investigación OperativaUniversidad de Santiago de CompostelaSpain

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