Abstract
In this article, the lifetime data subjecting to right random censoring is considered. Nonparametric estimation of the distribution function based on the conception of presmoothed estimation of relative-risk function and the properties of the estimator by using methods of numerical modeling are discussed. In the model under consideration, the estimates were compared using numerical methods to determine which of the estimates is actually better.
Highlights
Censored data occur in survival analysis, bio-medical trials, industrial experiments
The lifetime data subjecting to right random censoring is considered
Nonparametric estimation of the distribution function based on the conception of presmoothed estimation of relative-risk function and the properties of the estimator by using methods of numerical modeling are discussed
Summary
Censored data occur in survival analysis, bio-medical trials, industrial experiments. In [4] it was proposed several extended versions of estimator (2) in generalized models of incomplete observations mixed with competing risks. These estimators were extensively studied in some statistical problems. Estimator FnACL in PHM is asymptotically efficient with respect to FnPL This advantage of the estimator is well preserved for plug-in estimators of many functionals Cao et al [11] proposed following presmoothed PL-estimator of d.f. F by replacing the censoring indicators δ( j) in the expression of PL-estimator (1) by the estimator (5) at the observed data points:. We can see that estimator (7) is well defined in whole line without any conditions on censorship
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