Multiple comparison procedures with the average for normal distribution

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Title:	Multiple comparison procedures with the average for normal distribution
Other Titles:	常態分配與平均比較的多重比較程序
Authors:	吳淑妃;Wu, Shu-fei;Chen, Hubert J.
Contributors:	淡江大學統計學系
Keywords:	Probability requirement;better-than-the-average;Monte-Carlo techniques;Bonferroni inequality
Date:	1998-01-01
Issue Date:	2009-11-30 12:55:00 (UTC+8)
Publisher:	American Sciences Press
Abstract:	In this article we propose some multiple comparison procedures with the average. Simultaneous confidence intervals are considered for normal distributions with common known or unknown variances. These procedures can be used to identify better-than-the-average, worse-than-the-average and not-much-different-from-the-average products in agriculture, stock market, medical research, and auto models. The percentage points for singular multivariate normal and multivariate t distributions are investigated. Furthermore, the case of normal distributions under heteroscedasticity is also developed. An example is given.
Relation:	American journal of mathematical and management sciences 18(1-2), pp.193-218
DOI:	10.1080/01966324.1998.10737459
Appears in Collections:	[Graduate Institute & Department of Statistics] Journal Article

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