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Optimality of Quasi-Score in the multivariate mean-variance model with an application to the zero-inflated Poisson model with measurement errors

机译:准分数在多变量均值 - 方差模型的与应用程序与测量误差的零膨胀泊松模型最优

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摘要

In a multivariate mean-variance model, the class of linear score (LS) estimators based on an unbiased linear estimating function is introduced. A special member of this class is the (extended) quasi-score (QS) estimator. It is ``extended'' in the sense that it comprises the parameters describing the distribution of the regressor variables. It is shown that QS is (asymptotically) most efficient within the class of LS estimators. An application is the multivariate measurement error model, where the parameters describing the regressor distribution are nuisance parameters. A special case is the zero-inflated Poisson model with measurement errors, which can be treated within this framework.
机译:在多元平均方差模型中,介绍了基于无偏线性估计函数的线性得分(LS)估计器的类别。此类的一个特殊成员是(扩展)准得分(QS)估计器。从某种意义上说,它是``扩展的'',它包含描述回归变量分布的参数。结果表明,在LS估计量类别中,QS是(渐近地)最有效的。一个应用是多元测量误差模型,其中描述回归变量分布的参数是令人讨厌的参数。一种特殊情况是带有测量误差的零膨胀泊松模型,可以在此框架内对其进行处理。

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