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Boundary Bias Correction for Nonparametric Deconvolution

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  • Shunpu Zhang
  • Rohana Karunamuni

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  • Shunpu Zhang & Rohana Karunamuni, 2000. "Boundary Bias Correction for Nonparametric Deconvolution," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 52(4), pages 612-629, December.
    • Handle: RePEc:spr:aistmt:v:52:y:2000:i:4:p:612-629
    DOI: 10.1023/A:1017564907869
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    References listed on IDEAS

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    1. Stefanski, Leonard A., 1990. "Rates of convergence of some estimators in a class of deconvolution problems," Statistics & Probability Letters, Elsevier, vol. 9(3), pages 229-235, March.
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    Cited by:

    1. Jun Cai & William C. Horrace & Christopher F. Parmeter, 2021. "Density deconvolution with Laplace errors and unknown variance," Journal of Productivity Analysis, Springer, vol. 56(2), pages 103-113, December.
    2. William Horrace & Christopher Parmeter, 2011. "Semiparametric deconvolution with unknown error variance," Journal of Productivity Analysis, Springer, vol. 35(2), pages 129-141, April.
    3. Jesús Fajardo & Pedro Harmath, 2021. "Boundary estimation with the fuzzy set density estimator," METRON, Springer;Sapienza Università di Roma, vol. 79(3), pages 285-302, December.
    4. Delaigle, A. & Gijbels, I., 2006. "Data-driven boundary estimation in deconvolution problems," Computational Statistics & Data Analysis, Elsevier, vol. 50(8), pages 1965-1994, April.
    5. Yuhao Deng & Chong You & Yukun Liu & Jing Qin & Xiao‐Hua Zhou, 2021. "Estimation of incubation period and generation time based on observed length‐biased epidemic cohort with censoring for COVID‐19 outbreak in China," Biometrics, The International Biometric Society, vol. 77(3), pages 929-941, September.
    6. Yousri Slaoui, 2021. "Data-driven Deconvolution Recursive Kernel Density Estimators Defined by Stochastic Approximation Method," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(1), pages 312-352, February.

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