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Estimation of Functional Regression Models for Functional Responses by Wavelet Approximation

  • Ana Aguilera
  • Francisco Ocaña
  • Mariano Valderrama
Conference paper
Part of the Contributions to Statistics book series (CONTRIB.STAT.)

A linear regression model to estimate a sample of response curves (realizations of a functional response) from a sample of predictor curves (functional predictor) is considered. Difierent procedures for estimating the parameter function of the model based on wavelets expansions and functional principal component decomposition of both the predictor and response curves are proposed. Wavelets coeficients will be estimated from discrete observations of sample curves at irregularly spaced time points that could be difierent among sample individuals.

Keywords

Functional Response Discrete Wavelet Transform Multivariate Linear Regression Model Functional Data Analysis Orthonormal Wavelet 
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

  • Ana Aguilera
    • 1
  • Francisco Ocaña
    • 1
  • Mariano Valderrama
    • 1
  1. 1.Department of StatisticsO.R. University of GranadaSpain

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