一种基于ALD和AEP分布的贝叶斯分位数回归
A Bayesian Quantile Regression Based on ALD and AEP Distribution
DOI: 10.12677/AAM.2020.97125, PDF,   
作者: 李东升, 林 挺：贵州民族大学数据科学与信息工程学院，贵州 贵阳；吴有富：贵州交通职业技术学院，贵州 贵阳
关键词: 分位数回归；非对称指数幂分布；非对称拉普拉斯分布；吉布斯抽样；Quantile Regression； Asymmetric Exponential Power Distribution； Asymmetric Laplace Distribution； Gibbs Sampling
摘要: 本文采用非对称指数幂分布(AEP)与非对称拉普拉斯分布(ALD)对分位数回归模型的误差项进行假定，对此进行贝叶斯分位数回归的参数估计。针对参数后验密度的复杂性，采用吉布斯抽样算法，对ALD分布和AEP分布进行后验参数抽样。通过数值模拟结果可知，服从AEP分布的误差假定对数据的适应性比ALD分布的要强。
Abstract: In this paper, the asymmetric exponential power distribution (AEP) and asymmetric Laplace distribution (ALD) are used to make assumptions about the error terms of the quantile regression model, and the parameters of Bayesian quantile regression are estimated for this. Aiming at the complexity of the posterior density of parameters, the Gibbs sampling algorithm is used to sample the posterior parameters of the ALD distribution and AEP distribution. According to the numerical simulation results, the error following the AEP distribution is assumed to be more adaptable to the data than the ALD distribution.
文章引用：李东升, 吴有富, 林挺. 一种基于ALD和AEP分布的贝叶斯分位数回归[J]. 应用数学进展, 2020, 9(7): 1054-1065. https://doi.org/10.12677/AAM.2020.97125

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