TESTING FOR NORMAL ERRORS IN DESIGNS WITH MANY BLOCKS
成果类型：
Article
署名作者：
MEESTER, SG; LOCKHART, RA
署名单位：
University of Toronto; Simon Fraser University
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
发表日期：
1988
页码：
569575
关键词：
摘要：
Goodness-of-fit tests are provided for the assumption of homoscedastic normal errors in experimental designs where the number of fitted parameters is large. Asymptotic critical points are given for the Cramer-von Mises statistic, Watson''s statistic and the Anderson-Darling statistic. An expansion of the covariance function of the empirical process of standardized residuals is given. The corresponding weak convergence result is established for one-way layouts when the number of parameters grows linearly with the sample size. A Monte Carlo study is given to aid in the use of the tables.