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dc.contributor.authorKhan, Shahjahan
dc.contributor.authorBhatti, Ishaq
dc.date.accessioned2019-05-26T22:17:58Z
dc.date.available2019-05-26T22:17:58Z
dc.date.issued1998
dc.identifier.issn00963003en_US
dc.identifier.doi10.1016/S0096-3003(97)10100-Xen_US
dc.identifier.urihttp://hdl.handle.net/10072/121828
dc.description.abstractBeyond the customary analysis through the estimation and hypothesis testing about the parameters of the multiple regression models, often a natural interest is to predict the responses for a given set of values of the predictors. The main objective of this article is to obtain the prediction distribution for a set of future responses from a multiple linear regression model which follow equicorrelation structure. It derives the marginal likelihood estimate for the equicorrelation parameter, ρ, and then uses the invariant differentials to compute the joint distribution of the unobserved but realized future errors. The prediction distribution is derived by using the structural relation of the model. The main finding of this paper is that the prediction distribution turned out to be a Student-t which depends only on the estimated ρ and is invariant to the degrees of freedom of the original Student-t distribution.en_US
dc.description.peerreviewedYesen_US
dc.languageEnglishen_US
dc.publisherElsevier Scienceen_US
dc.publisher.placeUSAen_US
dc.relation.ispartofpagefrom205en_US
dc.relation.ispartofpageto217en_US
dc.relation.ispartofissue2-3en_US
dc.relation.ispartofjournalApplied Mathematics and Computationen_US
dc.relation.ispartofvolume95en_US
dc.titlePredictive Inference on Equicorrelated Linear Regression Modelsen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Peer Reviewed (HERDC)en_US
dc.type.codeC - Journal Articlesen_US
gro.facultyAn Unassigned Group, An Unassigned Departmenten_US
gro.hasfulltextNo Full Text
gro.griffith.authorBhatti, Ishaq


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