Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/71172
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dc.contributor.authorRahman, Azizuren
dc.date.issued2011en
dc.identifier.citationPioneer Journal of Theoretical and Applied Statistics, 2011; 1(2):99-112en
dc.identifier.urihttp://hdl.handle.net/2440/71172-
dc.description.abstractThe Bayesian methodology is used in this paper to derive the prediction distribution of future responses matrix for multivariate simple linear model with matrix-T error. Results reveal that the prediction distribution of future responses matrix is a matrix-T distribution with appropriate location, scale and shape parameters. The prediction distribution depends on the realized responses only through the sample regression matrix and the sample residual sum of squares and products matrix. The study model is robust and the Bayesian method is competitive with other statistical methods in the field of predictive inference. Some applications of predictive inference have also been illustrated.en
dc.description.statementofresponsibilityAzizur Rahmanen
dc.description.urihttp://www.pspchv.com/content_1_PJTAS_2.htmlen
dc.publisherPioneer Scientific Publisheren
dc.rights© Pioneer Scientific Publisheren
dc.subjectMatrix-T distribution; multivariate simple regression; Bayesian method; prediction distribution; β-expectation tolerance regionen
dc.titleBayesian predictive inference for multivariate simple regression model with matrix-T erroren
dc.typeJournal articleen
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