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Nonparametric density estimation based on the truncated mean

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  • Zhu, Ying

Abstract

Motivated by the optimality condition of a quantile loss minimization problem, a new family of closed-form density estimators based on truncated means is developed and found to achieve smaller mean squared errors in estimating the tails of the normal and gamma distributions when compared to the symmetric Rosenblatt–Parzen kernel estimator.

Suggested Citation

  • Zhu, Ying, 2013. "Nonparametric density estimation based on the truncated mean," Statistics & Probability Letters, Elsevier, vol. 83(2), pages 445-451.
    • Handle: RePEc:eee:stapro:v:83:y:2013:i:2:p:445-451
    DOI: 10.1016/j.spl.2012.10.023
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    References listed on IDEAS

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    1. Spanos,Aris, 1986. "Statistical Foundations of Econometric Modelling," Cambridge Books, Cambridge University Press, number 9780521269124.
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