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Covariance matrix estimation in the presence of auxiliary information

机译:存在辅助信息时的协方差矩阵估计

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摘要

Likelihood is one of the most important tools for statisticians and provides the main approach to inference in parametric models. It is also to derive nonparametric estimates and tests. Recently Owen (1988, 1990) has introduced an empirical likelihoodratio statistic for nonparametric problems and constructed the confidence regions of mean and some statistical functions. In many situations, however, we do not exactly know the distribution form, but we may have partial information about the distribution. For example, the population mean might equal some known value or have a functional relationship with the variance. Several researchers have studied how to use auxiliary information, e.g. Owen (1991), Haberman (1984), Qin (1991), McLeish and Small (1991), Kuk and Muk (1989), Godambe and Thompson (1989).
机译:可能性是统计学家最重要的工具之一,它提供了参数模型推断的主要方法。它还将推导出非参数估计和检验。最近,Owen(1988,1990)引入了非参数问题的经验似然统计,并构造了均值和一些统计函数的置信区域。但是,在许多情况下,我们并不完全知道分布形式,但是可能会有关于分布的部分信息。例如,总体平均值可能等于某个已知值,或者与方差具有函数关系。几位研究人员研究了如何使用辅助信息,例如Owen(1991),Haberman(1984),Qin(1991),McLeish and Small(1991),Kuk and Muk(1989),Godambe和Thompson(1989)。

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