TESTING EXPONENTIALITY BASED ON KULLBACK-LEIBLER INFORMATION

• 成果类型: Article
• 署名作者: EBRAHIMI, N; HABIBULLAH, M; SOOFI, ES
• 署名单位: University of Wisconsin System; University of Wisconsin System; University of Wisconsin Milwaukee
• 刊物名称: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
• ISSN/ISSBN: 1369-7412
• 发表日期: 1992
• 页码: 739-748
• 关键词: STATISTICS; GOODNESS; fit

摘要

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.