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Semiparametric smoothing splines

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  • Juan M. Rodriguez‐Poo

Abstract

In regression analysis, when no previous information about the statistical model is available, non‐parametric estimation methods are very useful since their requirements on the specification of the model are very few. However, if this information exists, these methods usually neglect to incorporate it. In this paper, we propose a non‐parametric regression technique that accounts for information about the underlying statistical model when this information is introduced through a known function. We also provide some theoretical properties and examples of this estimator. © 1998 John Wiley & Sons, Ltd.

Suggested Citation

  • Juan M. Rodriguez‐Poo, 1998. "Semiparametric smoothing splines," Applied Stochastic Models and Data Analysis, John Wiley & Sons, vol. 14(1), pages 1-10, March.
  • Handle: RePEc:wly:apsmda:v:14:y:1998:i:1:p:1-10
    DOI: 10.1002/(SICI)1099-0747(199803)14:13.0.CO;2-2
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