完整后设资料纪录
DC 栏位语言
dc.contributor.authorLin, SHen_US
dc.contributor.authorLee, JCen_US
dc.date.accessioned2014-12-08T15:18:20Z-
dc.date.available2014-12-08T15:18:20Z-
dc.date.issued2005-10-01en_US
dc.identifier.issn0378-3758en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.jspi.2004.02.018en_US
dc.identifier.urihttp://hdl.handle.net/11536/13228-
dc.description.abstractThe hypothesis testing and interval estimation are considered for the common mean of several normal populations when the variances are unknown and possibly unequal. A new generalized pivotal is proposed based on the best linear unbiased estimator of the common mean and the generalized inference. An exact confidence interval for the common mean is also derived. The generalized confidence interval is illustrated with two numerical examples. The merits of the proposed method are numerically compared with those of the existing methods with respect to their expected lengths, coverage probabilities and powers under different scenarios. (c) 2004 Published by Elsevier B.V.en_US
dc.language.isoen_USen_US
dc.subjectcoverage probabilityen_US
dc.subjectexpected lengthen_US
dc.subjectgeneralized pivotal quantityen_US
dc.subjectgeneralized test variableen_US
dc.subjectGraybill-Deal estimatoren_US
dc.subjectpoweren_US
dc.titleGeneralized inferences on the common mean of several normal populationsen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.jspi.2004.02.018en_US
dc.identifier.journalJOURNAL OF STATISTICAL PLANNING AND INFERENCEen_US
dc.citation.volume134en_US
dc.citation.issue2en_US
dc.citation.spage568en_US
dc.citation.epage582en_US
dc.contributor.department统计学研究所zh_TW
dc.contributor.department资讯管理与财务金融系
注:原资管所+财金所
zh_TW
dc.contributor.departmentInstitute of Statisticsen_US
dc.contributor.departmentDepartment of Information Management and Financeen_US
dc.identifier.wosnumberWOS:000230806000016-
dc.citation.woscount8-
显示于类别:Articles


文件中的档案:

  1. 000230806000016.pdf

If it is a zip file, please download the file and unzip it, then open index.html in a browser to view the full text content.