In the higher dimensional case, we give a sufficient condition, and also point out the connection between boundary representations and essential normality of modules.

在高维的情形，给出了一个充分条件，并且指出边界表示问题与模的本质正规性之间的密切联系。

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Given the asymptotic bias and the asymptotic variance of estimation, moreover obtained the asymptotic normality of the estimation under certain condition using small-block and large-block arguments.

给出非参数回归模型中估计量的渐近偏差和渐近方差，并在适当条件下利用大小分块的思想获得了该估计量的渐近正态性。

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Given the asymptotic bias and the asymptotic variance of estimation, moreover obtained the asymptotic normality of the estimation under certain condition using small-block and large-block arguments.

给出非参数回归模型中估计量的渐近偏差和渐近方差，并在适当条件下利用大小分块的思想获得了该估计量的渐近正态性。

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