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On estimation of a density function in multiplicative censoring

Author

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  • R. Zamini
  • V. Fakoor
  • M. Sarmad

Abstract

This paper considers non-parametric density estimation in the context of multiplicative censoring. A new estimator for the density function is proposed and consistency of the proposed estimator is investigated. Simulations are drawn to illustrate the results and to show how the estimator behaves for finite samples. Copyright Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • R. Zamini & V. Fakoor & M. Sarmad, 2015. "On estimation of a density function in multiplicative censoring," Statistical Papers, Springer, vol. 56(3), pages 661-676, August.
    • Handle: RePEc:spr:stpapr:v:56:y:2015:i:3:p:661-676
    DOI: 10.1007/s00362-014-0602-x
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    References listed on IDEAS

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    1. Wied, Dominik & Weißbach, Rafael, 2010. "Consistency of the kernel density estimator - a survey," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 53(1), pages 1-21.
    2. Dominik Wied & Rafael Weißbach, 2012. "Consistency of the kernel density estimator: a survey," Statistical Papers, Springer, vol. 53(1), pages 1-21, February.
    3. Abbaszadeh, Mohammad & Chesneau, Christophe & Doosti, Hassan, 2012. "Nonparametric estimation of density under bias and multiplicative censoring via wavelet methods," Statistics & Probability Letters, Elsevier, vol. 82(5), pages 932-941.
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    Cited by:

    1. Yu-Ye Zou & Han-Ying Liang, 2020. "CLT for integrated square error of density estimators with censoring indicators missing at random," Statistical Papers, Springer, vol. 61(6), pages 2685-2714, December.
    2. Ali Al-Sharadqah & Majid Mojirsheibani & William Pouliot, 2020. "On the performance of weighted bootstrapped kernel deconvolution density estimators," Statistical Papers, Springer, vol. 61(4), pages 1773-1798, August.

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