Skip to main content
Log in

Computing a family of reproducing kernels for statistical applications

  • Published:
Numerical Algorithms Aims and scope Submit manuscript

Abstract

For an open subset Ω of ℝ, an integer,m, and a positive real parameter τ, the Sobolev spacesH m (Ω) equipped with the norms: ∥u2=∫u(t)2dt+(1/τ2mu (m)(t)2 constitute a family of reproducing kernel Hilbert spaces. When Ω is an open interval of the real line, we describe the computation of their reproducing kernels. We derive explicit formulas for these kernels for all values ofm in the case of the whole real line, and form=1 andm=2 in the case of a bounded open interval.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. R. A. Adams,Sobolev Spaces (Academic Press, Harcourt Brace Jovanovich, 1975).

    Google Scholar 

  2. S. Agmon,Lectures on Elliptic Boundary Value Problems (D. Van Nostrand, Princeton, NJ, 1965).

    Google Scholar 

  3. N. Aronszajn, Theory of reproducing kernels, Transactions of the AMS 68 (1950) 3–404.

    Google Scholar 

  4. M. Atteia,Hilbertian Kernels and Spline Functions (North-Holland, Amsterdam, 1992).

    Google Scholar 

  5. A. Y. Bezhaev and V. A. Vasilenko,Variational Spline Theory (NCC Publisher, Novosibirsk, 1993). Special issue of NCC Bulletin 3.

    Google Scholar 

  6. M. Delecroix, M. Simioni and C. Thomas-Agnan, Functional estimation under shape constraints, Journal of Nonparametric Statistics 6 (1996) 69–89.

    Google Scholar 

  7. M. Duc-Jacquet, Approximation des fonctionnelles lineaires sur les espaces hilbertiens autoreproduisants, thesis, University of Grenoble, France (1973).

    Google Scholar 

  8. B. Silverman, Spline smoothing: the equivalent kernel method, Annals of Statistics 12 (1984) 898–916.

    Google Scholar 

  9. C. Thomas-Agnan, Spline functions and stochastic filtering, Annals of Statistics 19 (1991) 1512–1527.

    Google Scholar 

  10. G. Wahba and J. Wendelberger, Some new mathematical methods for variational objective analysis using splines and cross-validation, Monthly Weather Review (1980) 1122–1143.

  11. H. L. Weinert, eds.,Reproducing Kernel Hilbert Spaces: Applications in Statistical Signal Processing (Hutchinson Ross, Stroudsburg, PA, 1982).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Additional information

Communicated by P. J. Laurent

This research was partly supported by NSF Grant DMS-9002566.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Thomas-Agnan, C. Computing a family of reproducing kernels for statistical applications. Numer Algor 13, 21–32 (1996). https://doi.org/10.1007/BF02143124

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02143124

Keywords

AMS subject classification

Navigation