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Testing For Differences In Means Of Skewed Processes

 

作者: EdgemanRick,  

 

期刊: International Journal of Modelling and Simulation  (Taylor Available online 1992)
卷期: Volume 12, issue 1  

页码: 20-21

 

ISSN:0228-6203

 

年代: 1992

 

DOI:10.1080/02286203.1992.11760142

 

出版商: Taylor&Francis

 

关键词: Analysis of rcciprocals;inverse Gaussian distribution

 

数据来源: Taylor

 

摘要:

abstractStochastic models for many processes that arise in the life, physical, and engineering sciences must be able to accommodate skew. Among the more frequently used models of this sort are the extreme-value, gamma, inverse Gaussian, lognormal, and WeibuJl densities. Goodness–of–fit test generally have little ability W distinguish between these competing models, and the decision to adopt one model to the exclusion of the others may hinge on the inferential analysis procedures available for the adopted model. Among the previously listed models, the inverse Gaussian density offers a variety of analyses that are comparable to those available for the normal dislribution, such as regression, t-tests, confidence intervals, and an alternative to the analysis of variance (ANOYA) for skewed data. This alternative to ANOYA is refeITed to as analysis of reciprocals (ANORE) and provides the topic for this paper.

 

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