Methodology and Convergence Rates for Functional Linear Regression

@inproceedings{Hall2007MethodologyAC,
  title={Methodology and Convergence Rates for Functional Linear Regression},
  author={Peter W. Hall and Joel L. Horowitz},
  year={2007}
}
In functional linear regression, the slope “parameter” is a function. Therefore, in a nonparametric context, it is determined by an infinite number of unknowns. Its estimation involves solving an illposed problem and has points of contact with a range of methodologies, including statistical smoothing and deconvolution. The standard approach to estimating the slope function is based explicitly on functional principal components analysis and, consequently, on spectral decomposition in terms of… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 30 references

Functional Data Analysis. Springer, New York. FUNCTIONAL LINEAR REGRESSION

  • J. O. Ramsay, B. W. Silverman
  • 1997
Highly Influential
4 Excerpts

Robust estimation of generalized linear models with measurement errors

  • T. Li, C. Hsiao
  • J. Econometrics
  • 2004
1 Excerpt

Linear regression models for functional data. Available at www.quantlet.org/hizirjsp/sarda-cardot/sarda-cardot.pdf 22 P

  • H. Cardot, P. Sarda
  • HALL AND J. L. HOROWITZ
  • 2003
1 Excerpt

Applied Functional Data Analysis: Methods and Case Studies

  • J. O. Ramsay, B. W. Silverman
  • 2002
1 Excerpt

Estimation of integrated squared density derivatives from a contaminated sample

  • A. Delaigle, I. Gijbels
  • J. R. Stat. Soc. Ser. B Stat. Methodol
  • 2002
1 Excerpt

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