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Bagging of density estimators

Author

Listed:
  • Mathias Bourel

    (Universidad de la República
    Universidad de la República)

  • Jairo Cugliari

    (Université Lumière Lyon 2)

Abstract

In this work we give new density estimators by averaging classical density estimators such as the histogram, the frequency polygon and the kernel density estimators obtained over different bootstrap samples of the original data. Using existent results, we prove the $$L^2$$ L 2 -consistency of these new estimators and compare them to several similar approaches by simulations. Based on them, we give also a way to construct non-parametric pointwise variability band for the target density.

Suggested Citation

  • Mathias Bourel & Jairo Cugliari, 2019. "Bagging of density estimators," Computational Statistics, Springer, vol. 34(4), pages 1849-1869, December.
    • Handle: RePEc:spr:compst:v:34:y:2019:i:4:d:10.1007_s00180-019-00889-9
    DOI: 10.1007/s00180-019-00889-9
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    References listed on IDEAS

    as
    1. Ridgeway, Greg, 2002. "Looking for lumps: boosting and bagging for density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 38(4), pages 379-392, February.
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