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Paper detail

Hazard Estimation under Generalized Censoring

This paper focuses on the problem of the estimation of the cumulative hazard function of a distribution on a general complete separable metric space when the data points are subject to censoring by an arbitrary adapted random set. A problem involving observability of the estimator proposed in [8] and [9] is resolved and a functional central limit theorem is proven for the revised estimator. Several examples and applications are discussed, and the validity of bootstrap methods is established in each case.

preprint2008arXivOpen access
Alberto Carabarin AguirreB. Gail Ivanoff
math.STStatistics Theory
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Alberto Carabarin AguirreB. Gail Ivanoff

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