利用中位秩集合采样进行贝叶斯回归分析

IF 1 Q1 MATHEMATICS

European Journal of Pure and Applied Mathematics Pub Date : 2024-01-31 DOI:10.29020/nybg.ejpam.v17i1.5015

I. Nawajah, H. Kanj, Y. Kotb, Julian Hoxha, Mouhammad Alakkoumi, Kamel Jebreen

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引用次数: 0

摘要

通过采用中位秩集合采样（MRSS）对线性回归参数系统进行贝叶斯估计。可以得到完整的条件分布和相关的后验分布。因此，基于马尔可夫链蒙特卡罗模拟，确定了回归参数的贝叶斯点估计和可信区间。为了衡量所获得的贝叶斯估计值相对于频数估计值的效率，我们使用马尔可夫链蒙特卡罗模拟计算了所获得的贝叶斯估计值的渐近相对效率。

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Bayesian Regression Analysis using Median Rank Set Sampling

Bayesian estimation of the linear regression parameter system is considered by deploying Median Rank Set Sampling (MRSS). The full conditional distributions and the associated posterior distribution are obtained. Therefore, based on Markov Chain Monte Carlo simulation, the Bayesian point estimates and credible intervals for the regression parameters are determined. To measure the efficiency of the obtained Bayesian estimates concerning the frequentist estimates we compute the asymptotic relative efficiency of the obtained Bayesian estimates using Markov Chain Monte Carlo simulation.

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来源期刊

European Journal of Pure and Applied Mathematics MATHEMATICS-

CiteScore

1.30

自引率

28.60%

发文量

156