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A note on estimating cumulative distribution functions by the use of convolution power kernels

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  • Funke, Benedikt
  • Palmes, Christian

Abstract

Our paper investigates the nonparametric estimation of cumulative distribution functions of nonnegative valued random variables using convolution power kernels. Our proposed consistent estimator avoids boundary effects near the origin. We present its asymptotic properties and give a short simulation study.

Suggested Citation

  • Funke, Benedikt & Palmes, Christian, 2017. "A note on estimating cumulative distribution functions by the use of convolution power kernels," Statistics & Probability Letters, Elsevier, vol. 121(C), pages 90-98.
    • Handle: RePEc:eee:stapro:v:121:y:2017:i:c:p:90-98
    DOI: 10.1016/j.spl.2016.10.004
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    References listed on IDEAS

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    1. Alexandre Leblanc, 2012. "On estimating distribution functions using Bernstein polynomials," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(5), pages 919-943, October.
    2. Rong Liu & Lijian Yang, 2008. "Kernel estimation of multivariate cumulative distribution function," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 20(8), pages 661-677.
    3. Jones, M. C., 1990. "The performance of kernel density functions in kernel distribution function estimation," Statistics & Probability Letters, Elsevier, vol. 9(2), pages 129-132, February.
    4. Lloyd, Chris J. & Yong, Zhou, 1999. "Kernel estimators of the ROC curve are better than empirical," Statistics & Probability Letters, Elsevier, vol. 44(3), pages 221-228, September.
    Full references (including those not matched with items on IDEAS)

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