Correcting moments for goodness of fit tests based on two entropy estimates
The sample entropy (Vasicek, 1976) has been most widely used as a nonparametric entropy estimator due to its simplicity, but its underlying distribution function has not been known yet though its moments are required in establishing the entropy-based goodness of test statistic (Soofi et al, 1995). In this paper we derive the nonparametric distribution function of the sample entropy as a piece-wise uniform distribution in the lights of Theil (1980) and Dudwicz and van der Meulen (1987). Then we establish the entropy-based goodness of fit test statistics based on the nonparametric distribution functions of the sample entropy and modified sample entropy (Ebrahimi et al., 1994), and compare their performances for the exponential and normal distributions.
kullback-leibler information maximum entropy nonparametric kernel density estimation order statistics