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Maximum deviation of error density estimators in censored linear regression

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  • Cheng, Fuxia

Abstract

This paper considers the maximum deviation of the error density estimator in linear regression with right censored data. Based on the Kaplan–Meier estimator of the residual distribution, we define the kernel-smoothed estimator of an error density function. The limit distributions for the maximum deviation of the estimator are obtained.

Suggested Citation

  • Cheng, Fuxia, 2012. "Maximum deviation of error density estimators in censored linear regression," Statistics & Probability Letters, Elsevier, vol. 82(9), pages 1657-1664.
    • Handle: RePEc:eee:stapro:v:82:y:2012:i:9:p:1657-1664
    DOI: 10.1016/j.spl.2012.05.001
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    References listed on IDEAS

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    1. Diehl, Sabine & Stute, Winfried, 1988. "Kernel density and hazard function estimation in the presence of censoring," Journal of Multivariate Analysis, Elsevier, vol. 25(2), pages 299-310, May.
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    Cited by:

    1. Fuxia Cheng, 2017. "Asymptotic Properties of Hazard Rate Estimator in Censored Linear Regression," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 79(1), pages 1-12, February.

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