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Semi-functional partial linear regression

Author

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  • Aneiros-Pérez, Germán
  • Vieu, Philippe

Abstract

This note deals with the problem of predicting some real-valued response variable in the situation where some among the explanatory variables are functional. More precisely, a new model is introduced in order to capture both the advantages of a semi-linear modelling and those of the recent advances on nonparametric statistics for functional data. The aim of this note is to provide the first advances in this direction. After having constructed precisely the so-called semi-functional partially linear model, the estimates are presented and some asymptotic results (with rates of convergence) are given. Lastly, a real data example illustrates the usefulness of the model.

Suggested Citation

  • Aneiros-Pérez, Germán & Vieu, Philippe, 2006. "Semi-functional partial linear regression," Statistics & Probability Letters, Elsevier, vol. 76(11), pages 1102-1110, June.
    • Handle: RePEc:eee:stapro:v:76:y:2006:i:11:p:1102-1110
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    References listed on IDEAS

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    1. Schick, Anton, 1996. "Root-n consistent estimation in partly linear regression models," Statistics & Probability Letters, Elsevier, vol. 28(4), pages 353-358, August.
    2. Hardle, Wolfgang & LIang, Hua & Gao, Jiti, 2000. "Partially linear models," MPRA Paper 39562, University Library of Munich, Germany, revised 01 Sep 2000.
    3. Gao, Jiti, 1995. "The laws of the iterated logarithm of some estimates in partly linear models," Statistics & Probability Letters, Elsevier, vol. 25(2), pages 153-162, November.
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