文章基本信息

标题：Equivariance and Generalized Inference in Two-Sample Location-Scale Families
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作者：Sévérien Nkurunziza ; Fuqi Chen
期刊名称：Journal of Probability and Statistics
印刷版ISSN：1687-952X
电子版ISSN：1687-9538
出版年度：2011
卷号：2011
DOI：10.1155/2011/474826
出版社：Hindawi Publishing Corporation
摘要：We are interested in-typical Behrens-Fisher problem in general location-scale families. We present a method of constructing generalized pivotal quantity (GPQ) and generalized 𝑃 value (GPV) for the difference between two location parameters. The suggested method is based on the minimum risk equivariant estimators (MREs), and thus, it is an extension of the methods based on maximum likelihood estimators and conditional inference, which have been, so far, applied to some specific distributions. The efficiency of the procedure is illustrated by Monte Carlo simulation studies. Finally, we apply the proposed method to two real datasets.