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Strong uniform consistency of kernel density estimators under a censored dependent model

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  • Fakoor, V.

Abstract

Problems with censored data arise frequently in survival analyses and reliability applications. The estimation of the density function of the lifetimes is often of interest. In this paper, the estimation of the density function by the kernel method is considered, when censored data show some kind of dependence. We apply the strong Gaussian approximation technique for studying the strong uniform consistency for kernel estimators of the density function under a censored dependent model.

Suggested Citation

  • Fakoor, V., 2010. "Strong uniform consistency of kernel density estimators under a censored dependent model," Statistics & Probability Letters, Elsevier, vol. 80(5-6), pages 318-323, March.
    • Handle: RePEc:eee:stapro:v:80:y:2010:i:5-6:p:318-323
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    References listed on IDEAS

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    1. Masry, Elias & Tjøstheim, Dag, 1997. "Additive Nonlinear ARX Time Series and Projection Estimates," Econometric Theory, Cambridge University Press, vol. 13(2), pages 214-252, April.
    2. Masry, Elias & Tjøstheim, Dag, 1995. "Nonparametric Estimation and Identification of Nonlinear ARCH Time Series Strong Convergence and Asymptotic Normality: Strong Convergence and Asymptotic Normality," Econometric Theory, Cambridge University Press, vol. 11(2), pages 258-289, February.
    3. Cai, Zongwu, 1998. "Kernel Density and Hazard Rate Estimation for Censored Dependent Data," Journal of Multivariate Analysis, Elsevier, vol. 67(1), pages 23-34, October.
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