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Using non-stochastic terms to advantage in kernel-based estimation of integrated squared density derivatives

Author

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  • Jones, M. C.
  • Sheather, S. J.

Abstract

Improved kernel-based estimates of integrated squared density derivatives are obtained by reinstating non-stochastic terms that have previously been omitted, and using the bandwidth to (approximately) cancel these positive quantities with the leading smoothing bias terms which are negative. Such estimators have exhibited great practical merit in the context of data-based selection of the bandwidth in kernel density estimation, a motivating application of this work discussed elsewhere.

Suggested Citation

  • Jones, M. C. & Sheather, S. J., 1991. "Using non-stochastic terms to advantage in kernel-based estimation of integrated squared density derivatives," Statistics & Probability Letters, Elsevier, vol. 11(6), pages 511-514, June.
    • Handle: RePEc:eee:stapro:v:11:y:1991:i:6:p:511-514
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