Inference for ordered parameters in multinomial distributions
Inference for ordered parameters in multinomial distributions
复制标题
多项分布中有序参数的推断
DOI:
10.1007/s11425-008-0122-z
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发表时间:
2009-03
期刊:
影响因子:
--
通讯作者:
熊世峰
中科院分区:
文献类型:
--
作者:
熊世峰
This paper discusses inference for ordered parameters of multinomial distributions. We first show that the asymptotic distributions of their maximum likelihood estimators (MLEs) are not always normal and the bootstrap distribution estimators of the MLEs can be inconsistent. Then a class of weighted sum estimators (WSEs) of the ordered parameters is proposed. Properties of the WSEs are studied, including their asymptotic normality. Based on those results, large sample inferences for smooth functions of the ordered parameters can be made. Especially, the confidence intervals of the maximum cell probabilities are constructed. Simulation results indicate that this interval estimation performs much better than the bootstrap approaches in the literature. Finally, the above results for ordered parameters of multinomial distributions are extended to more general distribution models.
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