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Entropic kernels for data smoothing

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  • Bowden, Roger

Abstract

Data smoothing or regression kernels based on locational entropy embody the principle that observations towards the extremes of the chosen data window should provide less information than those at the midpoint. Weight patterns can be flexible, depending on the choice of prior information density.

Suggested Citation

  • Bowden, Roger, 2013. "Entropic kernels for data smoothing," Statistics & Probability Letters, Elsevier, vol. 83(3), pages 916-922.
    • Handle: RePEc:eee:stapro:v:83:y:2013:i:3:p:916-922
    DOI: 10.1016/j.spl.2012.12.006
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    References listed on IDEAS

    as
    1. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
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