The best test of exponentiality against singly truncated normal alternatives

• 成果类型: Article
• 署名作者: del Castillo, J; Puig, P
• 署名单位: Autonomous University of Barcelona
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.2307/2670173
• 发表日期: 1999
• 页码: 529-532
• 关键词: Asymptotics

摘要

we show that the likelihood ratio test of exponentiality against singly truncated normal alternatives is the uniformly most powerful unbiased test and can be expressed in terms of the sampling coefficient of variation. This test is closely related to Greenwood's statistic for testing departures from the uniform distribution. We provide a way to approximate the critical points of the test, using saddlepoint methods, that gives a high degree of accuracy.