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Bias and bandwidth for local likelihood density estimation

Author

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  • Otneim, Håkon
  • Karlsen, Hans Arnfinn
  • Tjøstheim, Dag

Abstract

A local likelihood density estimator is shown to have asymptotic bias depending on the dimension of the local parameterization. Comparing with kernel estimation it is demonstrated using a variety of bandwidths that we may obtain as good and potentially even better estimates using local likelihood. Boundary effects are also examined.

Suggested Citation

  • Otneim, Håkon & Karlsen, Hans Arnfinn & Tjøstheim, Dag, 2013. "Bias and bandwidth for local likelihood density estimation," Statistics & Probability Letters, Elsevier, vol. 83(5), pages 1382-1387.
    • Handle: RePEc:eee:stapro:v:83:y:2013:i:5:p:1382-1387
    DOI: 10.1016/j.spl.2013.02.003
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    References listed on IDEAS

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    1. Tjøstheim, Dag & Hufthammer, Karl Ove, 2013. "Local Gaussian correlation: A new measure of dependence," Journal of Econometrics, Elsevier, vol. 172(1), pages 33-48.
    2. Peter Hall & Terence Tao, 2002. "Relative efficiencies of kernel and local likelihood density estimators," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 537-547, August.
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    Cited by:

    1. Tata Subba Rao & Granville Tunnicliffe Wilson & Geir Drage Berentsen & Ricardo Cao & Mario Francisco-Fernández & Dag TjØstheim, 2017. "Some Properties of Local Gaussian Correlation and Other Nonlinear Dependence Measures," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(2), pages 352-380, March.

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