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المؤلفAlhamide, A.A.
المؤلفKAMARULZAMAN, Ibrahim
المؤلفAlodat, M.T.
المؤلفZin, WAN ZAWIAH WAN
تاريخ الإتاحة2020-06-23T20:45:40Z
تاريخ النشر2019
اسم المنشورSains Malaysiana
المصدرScopus
الرقم المعياري الدولي للكتاب1266039
معرّف المصادر الموحدhttp://dx.doi.org/10.17576/jsm-2019-4801-26
معرّف المصادر الموحدhttp://hdl.handle.net/10576/15102
الملخصA 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.
اللغةen
الناشرPenerbit Universiti Kebangsaan Malaysia
الموضوعABSTRAK
Alpha skew normal distribution
Bayesian linear regression model
Simulation
العنوانBayesian inference for linear regression under alpha-skew-normal prior [Pentaabiran Bayesian untuk Model Regresi Linear Prior Normal-Pencong-Alfa]
النوعArticle
الصفحات227-235
رقم العدد1
رقم المجلد48
dc.accessType Open Access


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