LARGE SAMPLE THEORY OF SPACINGS STATISTICS FOR TESTS OF FIT FOR THE COMPOSITE HYPOTHESIS

• 成果类型: Article
• 署名作者: WELLS, MT; JAMMALAMADAKA, SR; TIWARI, RC
• 署名单位: University of California System; University of California Santa Barbara; University of North Carolina; University of North Carolina Chapel Hill
• 刊物名称: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
• ISSN/ISSBN: 1369-7412
• 发表日期: 1993
• 页码: 189-203
• 关键词: goodness

摘要

Let X1, . . ., X(n) be a sequence of independent and identically distributed random variables with an unknown underlying continuous cumulative distribution function F. Often we would like to test a null hypothesis concerning the goodness of fit of F to some distribution function which is fully specified or belongs to some parametric family, i.e. in some applications the null hypothesis is simple whereas in others it may be composite. In this paper we present the large sample theory of tests based on non-symmetric functions of sample spacings under composite null hypotheses as well as under contiguous alternatives. Goodness-of-fit tests which are optimal within this class are constructed.