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Local Linear Functional Regression Based on Weighted Distance-based Regression

  • Eva Boj
  • Pedro Delicado
  • Josep Fortiana
Part of the Contributions to Statistics book series (CONTRIB.STAT.)

We consider the problem of nonparametrically predicting a scalar response variable yfrom a functional predictor . We have nobservations ( i yi). We assign a weight wi= K(d(   i)h) to each i, where dis a semimetric, Kis a kernel function and his the bandwidth. Then we fit a Weighted (Linear) Distance-Based Regression, where the weights are as above and the distances are given by a possibly difierent semi-metric.

Keywords

Weighted Little Square Weighted Version Mean Square Prediction Error Local Linear Regression Variable Bandwidth 
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

  • Eva Boj
    • 1
  • Pedro Delicado
    • 2
  • Josep Fortiana
    • 1
  1. 1.Universitat de BarcelonaSpain
  2. 2.Universitat Politècnica de CatalunyaSpain

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