Approximate MLE for the scale parameter of the generalized exponential distribution under random censoring

被引:0
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作者
Namhyun Kim
机构
[1] Hongik University,Department of Science
关键词
primary 62N02; secondary 62N01; Generalized exponential distribution; Kaplan-Meier estimator; Maximum likelihood estimator; Random censoring;
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摘要
In this paper, we consider the maximum likelihood estimator (MLE) of the scale parameter of the generalized exponential (GE) distribution based on a random censoring model. We assume the censoring distribution also follows a GE distribution. Since the estimator does not provide an explicit solution, we propose a simple method of deriving an explicit estimator by approximating the likelihood function. In order to compare the performance of the estimators, Monte Carlo simulation is conducted. The results show that the MLE and the approximate MLE are almost identical in terms of bias and variance.
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页码:119 / 131
页数:12
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