Bayesian inference for linear regression under alpha-skew-normal prior [Pentaabiran Bayesian untuk Model Regresi Linear Prior Normal-Pencong-Alfa]
Author | Alhamide, A.A. |
Author | KAMARULZAMAN, Ibrahim |
Author | Alodat, M.T. |
Author | Zin, WAN ZAWIAH WAN |
Available date | 2020-06-23T20:45:40Z |
Publication Date | 2019 |
Publication Name | Sains Malaysiana |
Resource | Scopus |
ISSN | 1266039 |
Abstract | A study on Bayesian inference for the linear regression model is carried out in the case when the prior distribution for the regression parameters is assumed to follow the alpha-skew-normal distribution. The posterior distribution and its associated full conditional distributions are derived. Then, the Bayesian point estimates and credible intervals for the regression parameters are determined based on a simulation study using the Markov chain Monte Carlo method. The parameter estimates and intervals obtained are compared with their counterparts when the prior distributions are assumed either normal or non-informative. In addition, the findings are applied to Scottish hills races data. It appears that when the data are skewed, the alpha-skew-normal prior contributes to a more precise estimate of the regression parameters as opposed to the other two priors. - 2019 Penerbit Universiti Kebangsaan Malaysia. All rights reserved. |
Language | en |
Publisher | Penerbit Universiti Kebangsaan Malaysia |
Subject | ABSTRAK Alpha skew normal distribution Bayesian linear regression model Simulation |
Type | Article |
Pagination | 227-235 |
Issue Number | 1 |
Volume Number | 48 |
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Mathematics, Statistics & Physics [726 items ]