A characterization of the Pareto distribution based on the Fisher information for censored data under non-regularity conditions

被引：0
作者：
George Tzavelas
机构：
[1] University of Piraeus,Department of Statistics and Insurance Sciences
来源：
Metrika | 2019年 / 82卷
关键词：
Fisher information; Type-I censoring; Random censoring; Scale parameter;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
It is proved that within a proper class of distributions, the Pareto and the shifted exponential distribution are the only distributions with the property of no loss of information due to type-I censoring and random censoring. The equality of the information before and after censoring it is achieved only when the regularity conditions do not hold.
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页码：429 / 440
页数：11
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