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Semi-parametric survival function estimators deduced from an identifying Volterra type integral equation

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  • Dikta, Gerhard
  • Reißel, Martin
  • Harlaß, Carsten

Abstract

Based on an identifying Volterra type integral equation for randomly right censored observations from a lifetime distribution function F, we solve the corresponding estimating equation by an explicit and implicit Euler scheme. While the first approach results in some known estimators, the second one produces new semi-parametric and pre-smoothed Kaplan–Meier estimators which are real distribution functions rather than sub-distribution functions as the former ones are. This property of the new estimators is particular useful if one wants to estimate the expected lifetime restricted to the support of the observation time.

Suggested Citation

  • Dikta, Gerhard & Reißel, Martin & Harlaß, Carsten, 2016. "Semi-parametric survival function estimators deduced from an identifying Volterra type integral equation," Journal of Multivariate Analysis, Elsevier, vol. 147(C), pages 273-284.
    • Handle: RePEc:eee:jmvana:v:147:y:2016:i:c:p:273-284
    DOI: 10.1016/j.jmva.2016.02.008
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    References listed on IDEAS

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    1. Subramanian, Sundarraman, 2011. "Multiple imputations and the missing censoring indicator model," Journal of Multivariate Analysis, Elsevier, vol. 102(1), pages 105-117, January.
    2. Dikta, Gerhard & Kvesic, Marsel & Schmidt, Christian, 2006. "Bootstrap Approximations in Model Checks for Binary Data," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 521-530, June.
    3. Dikta, Gerhard, 2014. "Asymptotically efficient estimation under semi-parametric random censorship models," Journal of Multivariate Analysis, Elsevier, vol. 124(C), pages 10-24.
    4. Mondal, Shoubhik & Subramanian, Sundarraman, 2014. "Model assisted Cox regression," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 281-303.
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