Semiparametric smoothing splines

Juan M. Rodriguez‐Poo

Applied Stochastic Models and Data Analysis, 1998, vol. 14, issue 1, 1-10

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.

Date: 1998
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1002/(SICI)1099-0747(199803)14:13.0.CO;2-2

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:apsmda:v:14:y:1998:i:1:p:1-10

Access Statistics for this article

More articles in Applied Stochastic Models and Data Analysis from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().