Bootstrapping a consistent nonparametric goodness-of-fit test
用参数自举法逼近Fan(1994)中拟合优度检验统计量的有限样本分布，证明自举分布依概率收敛于渐近分布，模拟显示在仅25个观测值的小样本下表现极好且对核密度估计的平滑参数稳健。
Abstract In this paper, we employ the parametric bootstrap to approximate the finite sample distribution of a goodness-of-fit test statistic in Fan (1994). We show that the proposed bootstrap procedure works in that the bootstrap distribution conditional on the random sample tends to the asymptotic distribution of the test statistic in probability. A simulation study demonstrates that the bootstrap approximation works extremely well in small samples with only 25 observations and is very robust to the value of the smoothing parameter in the kernel density estimation. Keywords: BootstrapGoodness-Oe-Fit TestKernel Density EstimaitionSizePower