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Wavelet density deconvolution estimations with heteroscedastic measurement errors

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  • Zeng, Xiaochen
  • Wang, Jinru

Abstract

This paper discusses the mean consistency of both theoretical and practical wavelet estimators under deconvolution model with heteroscedastic measurement errors. When the model degenerates to the classical deconvolution problem, our results coincide with Geng & Wang’s theorem (2015).

Suggested Citation

  • Zeng, Xiaochen & Wang, Jinru, 2018. "Wavelet density deconvolution estimations with heteroscedastic measurement errors," Statistics & Probability Letters, Elsevier, vol. 134(C), pages 79-85.
    • Handle: RePEc:eee:stapro:v:134:y:2018:i:c:p:79-85
    DOI: 10.1016/j.spl.2017.10.016
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    References listed on IDEAS

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    1. Staudenmayer, John & Ruppert, David & Buonaccorsi, John P., 2008. "Density Estimation in the Presence of Heteroscedastic Measurement Error," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 726-736, June.
    2. Kerkyacharian, G. & Picard, D., 1992. "Density estimation in Besov spaces," Statistics & Probability Letters, Elsevier, vol. 13(1), pages 15-24, January.
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