在较弱的条件下,建立了可加分量最近邻估计和核估计的平均偏差的指数界。
Under mild conditions the exponential bounds of mean error for these estimates are established.
在这篇文章中,我们提出了最近邻估计在任意紧集上一致强收敛速度的概念,得到了一些较好的收敛速度。
In this paper, we propose the concept of rates of strong uniform convergence of nearest neighbor density estimates on any compact set and obtain some better convergence rates.
第一章介绍了最近邻密度估计的背景、意义、研究现状以及国内外有关最近邻密度估计的研究成果。
In chapter one, we introduced some background material and research results that have obtained of the nearest neighbor density estimator.
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