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参数需要估计时基于经验特征函数的拟合优度检验
SUMMARY The goodness-of-fit test using the empirical characteristic function proposed by Koutrouvelis (1980) is extended to the case where parameters must be estimated. The proposed test statistic is shown to have an asymptotic chi-squared distribution with degrees of freedom reduced by the number of parameters estimated.
基于经验特征函数的简单假设拟合优度检验
The empirical characteristic function φ n ( t ) and its asymptotic distribution are utilized to find a chi-squared goodness-of-fit test for simple null hypotheses. In addition the optimum number and location of points t at which φ n ( t ) has to be evaluated is investigated for specified alternative hypotheses.
基于经验特征函数的简单假设拟合优度检验
The empirical characteristic function φ n ( t ) and its asymptotic distribution are utilized to find a chi-squared goodness-of-fit test for simple null hypotheses. In addition the optimum number and location of points t at which φ n ( t ) has to be evaluated is investigated for specified alternative hypotheses.