Prediction distribution for linear regression model with multivariate Student-t errors under the Bayesian approach

Rahman, Azizur and Khan, Shahjahan (2007) Prediction distribution for linear regression model with multivariate Student-t errors under the Bayesian approach. In: 3rd International Conference on Research and Education in Mathematics (ICREM3), 10-12 April 2007, Kuala Lumpur, Malaysia.

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Abstract

[Abstract]: Prediction distribution is a basis for predictive inferences applied in many real world situations. It is a distribution of the unobserved future response(s) conditional on a set of realized responses from an informative experiment. Various statistical approaches can be used to obtain prediction distributions for different models. This study derives the prediction distribution(s) for multiple linear regression model using the Bayesian method when the error components of both the performed and future models have a multivariate Student-t distribution. The study observes that the prediction distribution(s) of future response(s) has a multivariate Student-t distribution whose degrees of freedom depends on the size of the realized sample and the dimension of the regression parameters’ vector but does not depend on the degrees of freedom of the errors distribution.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: No evidence of copyright restrictions on web site.
Depositing User: Professor Shahjahan Khan
Faculty / Department / School: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 11 Oct 2007 01:06
Last Modified: 02 Jul 2013 22:44
Uncontrolled Keywords: prediciton distribution, uniform prior, multivariate Student-t distribution
Fields of Research (FOR2008): 01 Mathematical Sciences > 0104 Statistics > 010405 Statistical Theory
URI: http://eprints.usq.edu.au/id/eprint/2446

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