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A Cramer-Rao type inequality for estimating a hazard with censoring

Abstract : Two very active areas of statistical research are non-parametric function estimation and analysis of censored survival data. A minimax asymptotic rate of convergence for the estimation of a hazard is obtained, in the presence of random right censoring using the link between the Kullback–Leibler distance of two probabilities and a weighted Lp-type distance between their corresponding hazards.
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Contributor : Catherine Huber Connect in order to contact the contributor
Submitted on : Tuesday, January 24, 2017 - 4:19:28 PM
Last modification on : Thursday, October 1, 2020 - 9:46:45 AM


  • HAL Id : hal-01445206, version 1



Catherine Huber-Carol. A Cramer-Rao type inequality for estimating a hazard with censoring. 2017 Conference Lifetime Data Science on Precision Medicine and Risk Analysis with Lifetime Data, Mei-Cheng Wang, Johns Hopkins University, May 2017, Storrs CT, United States. ⟨hal-01445206⟩



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