Asymptotically Chi-Squared Distributed Tests of Normality for Type II Censored Samples
作者:
VincentN. Lariccia,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1986)
卷期:
Volume 81,
issue 396
页码: 1026-1031
ISSN:0162-1459
年代: 1986
DOI:10.1080/01621459.1986.10478368
出版商: Taylor & Francis Group
关键词: Order statistics;Power;Goodness of fit
数据来源: Taylor
摘要:
A method is proposed for testing normality, in the case of general Type II censored data—that is, data for which only a subset of the order statistics are available. Three test statistics are proposed, which are generalizations of the statistics proposed in LaRiccia (1986), and have many of the same properties. Specifically, they are designed to be asymptotically optimal with respect to specific alternatives and are easily adjusted to be asymptotically optimal with respect to many other types of alternatives. Under the null hypothesis, irrespective of the type or amount of censoring, the proposed test statistics are asymptotically distributed as chi-squared random variables. Further, results of a simulation study are presented, indicating that these statistics converge quite rapidly in distribution to the appropriate chi-squared random variables and that the asymptotic critical values provide a useful approximation to the small sample critical values even forn= 25. The results of a simulation study comparing the power of the proposed tests with some standard tests of normality are presented. These results indicate that, for the cases considered, these statistics compare favorably with the standard procedures.
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