Gap-ratio goodness of fit tests for weibull or extreme value distribution assumptions with left or right censored data
作者:
Eric W. B. Gibson,
James J. Higgins,
期刊:
Communications in Statistics - Simulation and Computation
(Taylor Available online 2000)
卷期:
Volume 29,
issue 2
页码: 541-557
ISSN:0361-0918
年代: 2000
DOI:10.1080/03610910008813627
出版商: Marcel Dekker, Inc.
关键词: Omnibus test;type I censoring;type II censoring;order statistics;spacings;power
数据来源: Taylor
摘要:
With data collection in environmental science and bioassay, left censoring because of nondetects is a problem. Similarly in reliability and life data analysis right censoring frequently occurs. There is a need for goodness of fit tests that can adapt to left or right censored data and be used to check important distributional assumptions without becoming too difficult to regularly implement in practice. A new test statistic is derived from a plot of the standardized spacings between the order statistics versus their ranks. Any linear or curvilinear pattern is evidence against the null distribution. When testing the Weibull or extreme value null hypothesis this statistic has a null distribution that is approximatelyFfor most combinations of sample size and censoring of practical interest. Our statistic is compared to the Mann-Scheuer-Fertig statistic which also uses the standardized spacings between the order statistics. The results of a simulation study show the two tests are competitive in terms of power. Although the Mann-Scheuer-Fertig statistic is somewhat easier to compute, our test enjoys advantages in the accuracy of theFapproximation and the availability of a graphical diagnostic.
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