ASYMPTOTIC PROPERTIES OF MLE FOR WEIBULL DISTRIBUTION WITH GROUPED DATA

被引：0

作者：

机构：

来源：

Journal of Systems Science & Complexity | 2002年 / 02期

基金：

中国国家自然科学基金;

关键词：

Grouped data; MLE; Weibull distribution; identifiable; strongly consistent; asymptotically normal; the law of iterated logarithm; Newton iteration arithmetic;

D O I：

暂无

中图分类号：

O211 [概率论（几率论、或然率论）];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Abstract. A grouped data model for Weibull distribution is considered. Under mild con-ditions, the maximum likelihood estimators(MLE) are shown to be identifiable, stronglyconsistent, asymptotically normal, and satisfy the law of iterated logarithm. Newton iter-ation algorithm is also considered, which converges to the unique solution of the likelihoodequation. Moreover, we extend these results to a random case.

引用

页码：176 / 186

页数：11

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