Generalized weighted likelihood density estimators with application to finite mixture of exponential family distributions.
Generalized weighted likelihood density estimators with application to finite mixture of exponential family distributions.
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DOI：
10.1016/j.csda.2010.05.013
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发表时间：
2011-01-01
影响因子：
1.8
通讯作者：
Iglewicz B
中科院分区：
文献类型：
--
作者：
Zhan T;Chevoneva I;Iglewicz B
加权似然估计量家族在很大程度上与最小散度估计量重叠。与 MLE 相比，它们对数据污染具有鲁棒性。我们定义了一类广义加权似然估计（GWLE），提供其影响函数并讨论效率要求。我们引入了一种新的截断立方逆权重，它具有一阶和二阶效率，并且比之前报告的权重更稳健。我们还讨论了为迭代算法选择平滑带宽和加权起始值的新方法。通过对大重叠、重污染的三组分正态混合物模型的模拟研究，说明了截断立方逆权重的优点。还提供了真实的数据示例。
The family of weighted likelihood estimators largely overlaps with minimum divergence estimators. They are robust to data contaminations compared to MLE. We define the class of generalized weighted likelihood estimators (GWLE), provide its influence function and discuss the efficiency requirements. We introduce a new truncated cubic-inverse weight, which is both first and second order efficient and more robust than previously reported weights. We also discuss new ways of selecting the smoothing bandwidth and weighted starting values for the iterative algorithm. The advantage of the truncated cubic-inverse weight is illustrated in a simulation study of three-components normal mixtures model with large overlaps and heavy contaminations. A real data example is also provided.
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影响因子：
3.7
作者：
Markatou, M;Basu, A;Lindsay, BG
通讯作者：
Lindsay, BG
DOI：
10.1111/1467-9868.00095
发表时间：
1997-01-01
期刊：
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-METHODOLOGICAL
影响因子：
--
作者：
Richardson, S;Green, PJ
通讯作者：
Green, PJ
影响因子：
1.8
作者：
Basu, A;Lindsay, BG
通讯作者：
Lindsay, BG
DOI：
10.1198/016214501753382255
发表时间：
2001-12-01
影响因子：
3.7
作者：
Ishwaran, H;James, LF;Sun, JY
通讯作者：
Sun, JY
影响因子：
0.9
作者：
Fujisawa, Hironori;Eguchi, Shinto
通讯作者：
Eguchi, Shinto