A comparison of related density-based minimum divergence estimators
A comparison of related density-based minimum divergence estimators
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DOI：
10.1093/biomet/88.3.865
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发表时间：
2001-09-01
期刊：
影响因子：
2.7
通讯作者：
Basu, A
中科院分区：
文献类型：
--
作者：
Jones, MC;Hjort, NL;Basu, A
本文比较了Basu等人（1998）的最小散度估计和另一个竞争最小散度估计，后者与温德姆（1995）从不同角度提出的方法等价。这两种方法都可以应用于任何参数模型，并包含作为特殊情况的最大似然。比较了模型条件下的效果，并研究了鲁棒性。总的来说，这两种方法被发现执行非常相似。前一种方法比后者的一些相对较小的优势被确定。
This paper compares the minimum divergence estimator of Basu et al. (1998) to a competing minimum divergence estimator which turns out to be equivalent to a method proposed from a different perspective by Windham (1995). Both methods can be applied for any parametric model and contain maximum likelihood as a special case. Efficiencies are compared under model conditions, and robustness properties are studied. Overall the two methods are found to perform quite similarly. Some relatively small advantages of the former method over the latter are identified.