Skip to main content
Log in

A note on superkernel density estimators

  • Published:
Mathematical Methods of Statistics Aims and scope Submit manuscript

Abstract

It is well known that so-called superkernel density estimators have better asymptotic properties than conventional kernel estimators (and generally finite-order estimators) in the case when the density to be estimated is very smooth. In this note, we study asymptotic behavior of the mean integrated square error of superkernel density estimators in the case when the density to be estimated is not very smooth. It turns out that in this case, superkernel estimators still have better asymptotics than finite-order estimators.

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. J. E. Chancón, J. Montanero, and A. G. Nogales, “A Note on Kernel Density Estimation at a Parametric Rate”, J. Nonparam. Statist. 9, 13–21 (2007).

    Article  Google Scholar 

  2. K. B. Davis, “Mean Square Error Properties of Density Estimates”, Ann. Statist. 3, 1025–1030 (1975).

    Article  MathSciNet  MATH  Google Scholar 

  3. K. B. Davis, “Mean Integrated Square Error Properties of Density Estimates”, Ann. Statist. 5, 530–535 (1977).

    Article  MathSciNet  MATH  Google Scholar 

  4. L. Devroye, “A Note on the Usefulness of Superkernels in Density Estimates”, Ann. Statist. 20, 2037–2056 (1992).

    Article  MathSciNet  MATH  Google Scholar 

  5. E. Lukacs, Characteristic Functions (Griffin, London, 1970).

    MATH  Google Scholar 

  6. V. V. Petrov, Sums of Independent Random Variables (Springer, New York, 1975).

    Google Scholar 

  7. D. N. Politis, “Adaptive Bandwidth Choice”, J. Nonparam. Statist. 15, 517–533 (2003).

    Article  MathSciNet  MATH  Google Scholar 

  8. D. N. Politis and J. P. Romano, “Multivariate Density Estimation with General Flat-Top Kernels of Infinite Order”, J. Multivariate Anal. 68, 1–25 (1999).

    Article  MathSciNet  MATH  Google Scholar 

  9. M. P. Wand and M. C. Jones, Kernel Smoothing (Chapman and Hall, London, 1995).

    MATH  Google Scholar 

  10. G. S. Watson and M. R. Leadbetter, “On the Estimation of the Probability Density. I”, Ann. Math. Statist. 33, 480–491 (1963).

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to N. G. Ushakov.

About this article

Cite this article

Ushakov, N.G. A note on superkernel density estimators. Math. Meth. Stat. 21, 61–68 (2012). https://doi.org/10.3103/S1066530712010048

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3103/S1066530712010048

Keywords

2000 Mathematics Subject Classification

Navigation