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Seemingly Unrelated Nonparametric Model with the Measurement Error Data Problem

机译:带有测量误差数据问题的看似无关的非参数模型

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In this paper, by the deconvolution kernel density estimator their simple local regression version of the seemingly unrelated nonparametric regression model can be extended to the measurement error data where variance of disturbance in an equation is larger than that in the preceding one and all of the correlation coefficients between the disturbances across the equations are positive. The resulting convergence rates of the estimators are obtained and are shown to achieve the optimal rates of convergence.
机译:在本文中,通过反卷积核密度估计器,它们看似无关的非参数回归模型的简单局部回归版本可以扩展到测量误差数据,其中方程中的扰动方差大于前一个,所有相关方程之间的扰动之间的系数为正。获得估计器的最终收敛率,并显示出达到最佳收敛率。

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