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Deficiency of the mle of a smooth survival function under the proportional hazard model
Authors:JK Ghorai
Institution:University of Wisconsin-Milwaukee , Milwaukee, Wisconsin
Abstract:The problem of estimating a smooth distribution function F at a point t is treated under the proportional hazard model of random censorship. It is shown that a certain class of properly chosen kernel type estimator of F asymptotically perform better than the maximum likelihood estimator. It is shown that the relative deficiency of the maximum likelihood estimator of F under the proportional hazard model with respect to the properly chosen kernel type estimator tends to infinity as the sample size tends to infinity.
Keywords:Survival function  proportional hazard model  kernel type estimator  deficiency
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