Testing Exponentiality Based on Kullback-Leibler Information
提出一种基于Kullback-Leibler信息估计的指数分布拟合优度检验方法，通过Vasicek熵估计和蒙特卡洛模拟确定窗口大小与临界值，模拟显示该方法在多种备择假设下检验功效优于其他标准检验。
SUMMARY In this paper a test of fit for exponentiality based on the estimated Kullback-Leibler information is proposed. The procedure is applicable when the exponential parameter is or is not specified under the null hypothesis. The test uses the Vasicek entropy estimate, so to compute it a ‘window size’ m must first be fixed. A procedure for choosing m for various sample sizes is proposed and corresponding critical values are computed by Monte Carlo simulations. The use of the proposed test is shown in an illustrative example. Also, by means of Monte Carlo simulations, the power of the proposed test under various alternatives is compared with that of other standard tests. The results are impressive and the proposed test, almost always, has higher power than that of the other tests considered.