基于R^d上核密度估计的对称检验的大偏差
Large Deviations for a Test of Symmetry based on Kernel Density Estimator in R^d
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摘要: 设是基于一个核函数和取值于的独立同分布随机变量列的一个非参数核密度估计. 本文推广了在He和Gao(2008)中相应大偏差的结果, 即证明统计量的大偏差.Abstract: Let be a non-parametric kernel density estimator based on a kernel function and a sequence of independent and identically distributed random variables taking values in . The goal of this article is to extend the large deviations results in He and Gao (2008), i.e., to prove large deviations for the statistic .