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Goodness-of-fit tests based on empirical characteristic functions

机译:基于经验特征函数的拟合优度检验

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摘要

A class of goodness-of-fit tests based on the empirical characteristic function is studied. They can be applied to continuous as well as to discrete or mixed data with any arbitrary fixed dimension. The tests are consistent against any fixed alternative for suitable choices of the weight function involved in the definition of the test statistic. The bootstrap can be employed to estimate consistently the null distribution of the test statistic. The goodness of the bootstrap approximation and the power of some tests in this class for finite sample sizes are investigated by simulation.
机译:研究了基于经验特征函数的一类拟合优度检验。它们可以应用于具有任意固定尺寸的连续数据以及离散数据或混合数据。对于适当选择的测试统计量定义中的权重函数,这些测试与任何固定的替代方法都一致。引导程序可用于一致地估计测试统计量的零分布。通过仿真研究了bootstrap逼近的优缺点以及此类中对于有限样本量的某些测试的功效。

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