Skip to main content

Part of the book series: Springer Series in Statistics ((SSS))

  • 1782 Accesses

Abstract

Using the notation K h (·) to denote (1/h)K(·/h), let the univariate kernel estimate with bandwidth h > 0 and kernel K be

$$ {f_{n,K,h}}(x) = \frac{1}{n}\sum\limits_{i = 1}^n {{K_h}} (x - {X_i}).$$

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 159.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

§16.7. References

  • M. S. Bartlett, “Statistical estimation of density functions,” Sankhya Series A, vol. 25, pp. 245–254, 1963.

    MathSciNet  MATH  Google Scholar 

  • A. Berlinet, “Hierarchies of higher order kernels,” Probability Theory and Related Fields, vol. 94, pp. 489–504, 1993.

    Article  MathSciNet  MATH  Google Scholar 

  • K. B. Davis, “Mean square error properties of density estimates,” Annals of Statistics, vol. 5, pp. 1025–1030, 1975.

    Article  Google Scholar 

  • K. B. Davis, “Mean integrated square error properties of density estimates,” Annals of Statistics, vol. 5, pp. 530–535, 1977.

    Article  MathSciNet  MATH  Google Scholar 

  • L. Devroye, “Asymptotic performance bounds for the kernel estimate,” Annals of Statistics, vol. 16, pp. 1162–1179, 1988.

    Article  MathSciNet  MATH  Google Scholar 

  • L. Devroye, “A universal lower bound for the kernel estimate,” Statistics and Probability Letters, vol. 8, pp. 419–423, 1989.

    Article  MathSciNet  MATH  Google Scholar 

  • L. Devroye, “Universal smoothing factor selection in density estimation: theory and practice (with discussion),” Test, vol. 6, pp. 223–320, 1997.

    Article  MathSciNet  MATH  Google Scholar 

  • L. Devroye, A Course In Density Estimation, Birkhäuser-Verlag, Boston, 1987.

    MATH  Google Scholar 

  • L. Devroye and L. Györfi, Nonparametric Density Estimation. The L 1 View, Wiley, New York, 1985.

    Google Scholar 

  • L. Devroye and C. S. Penrod, “Distribution-free lower bounds in density estimation,” Annals of Statistics, vol. 12, pp. 1250–1262, 1984.

    Article  MathSciNet  MATH  Google Scholar 

  • T. Gasser, H.-G. Müller, and V. Mammitzsch, “Kernels for nonparametric curve estimation,” Journal of the Royal Statistical Society, Series B, vol. 47, pp. 238–252, 1985.

    MATH  Google Scholar 

  • B. L. Granovsky and H.-G. Müller, “On the optimality of a class of polynomial kernel functions,” Statistics and Decisions, vol. 7, pp. 301–312, 1989.

    MathSciNet  MATH  Google Scholar 

  • P. Hall and J. S. Marron, “Choice of kernel order in density estimation,” Annals of Statistics, vol. 16, pp. 161–173, 1988.

    Article  MathSciNet  MATH  Google Scholar 

  • H.-G. Müller, “Smooth optimum kernel estimators of densities, regression curves and modes,” Annais of Statistics, vol. 12, pp. 766–774, 1984.

    Article  MATH  Google Scholar 

  • W. Stuetzle and Y. Mittal, “Some comments on the asymptotic behavior of robust smoothers,” in: Proceedings of the Heidelberg Workshop (edited by T. Gasser and M. Rosenblatt), pp. 191–195, Springer Lecture Notes in Mathematics 757, Springer-Verlag, Heidelberg, 1979.

    Google Scholar 

  • G. S. Watson and M. R. Leadbetter, “On the estimation of the probability density,” Annais of Mathematical Statistics, vol. 34, pp. 480–491, 1963.

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2001 Springer Science+Business Media New York

About this chapter

Cite this chapter

Devroye, L., Lugosi, G. (2001). Choosing the Kernel Order. In: Combinatorial Methods in Density Estimation. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4613-0125-7_16

Download citation

  • DOI: https://doi.org/10.1007/978-1-4613-0125-7_16

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4612-6527-6

  • Online ISBN: 978-1-4613-0125-7

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics