ANALISIS REGRESI BAYES LINEAR SEDERHANA DENGAN PRIOR NONINFORMATIF
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https://doi.org/10.24843/MTK.2014.v03.i02.p064
Abstrak
The aim of this study is to apply Bayesian simple linear regression using noninformative prior. The data used in this study is 30 observational data with error generated from normal distribution. The noninformative prior was formed using Jeffreys’ rule. Computation was done using the Gibbs Sampler algorithm with 10.000 iteration. We obtain the following estimates for the parameters, with 95% Bayesian confidence interval (0,775775; 2,626025), with 95% Bayesian confidence interval (2,948; 3,052), and with 95% Bayesian confidence interval (0,375295; 1,114). These values are not very different compared to the actual value of the parameters.
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Diterbitkan
2014-05-31
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ISWARI, ANAK AGUNG ISTRI AGUNG CANDRA; SUMARJAYA, I WAYAN; SRINADI, I GUSTI AYU MADE.
ANALISIS REGRESI BAYES LINEAR SEDERHANA DENGAN PRIOR NONINFORMATIF.
E-Jurnal Matematika, [S.l.], v. 3, n. 2, p. 38 - 44, may 2014.
ISSN 2303-1751. Tersedia pada: <https://ojs.unud.ac.id./index.php/mtk/article/view/9604>. Tanggal Akses: 21 apr. 2025
doi: https://doi.org/10.24843/MTK.2014.v03.i02.p064.
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Articles
Kata Kunci
Bayesian regression; noninformative prior; Jeffreys’ rule; the Gibbs Sampler algorithm
This work is licensed under a Creative Commons Attribution 4.0 International License.
