| 基于DMC方法的城市空气质量SUR模型研究 |
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| 引用本文： | 乔杉,谢胜蓝,刘金山,夏强.基于DMC方法的城市空气质量SUR模型研究[J].数理统计与管理,2017(6):983-992. |
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| 作者姓名： | 乔杉 谢胜蓝 刘金山 夏强 |
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| 作者单位： | 华南农业大学数学与信息学院,广东广州,510642 |
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| 基金项目： | 国家自然科学基金资助项目(1171117)，全国统计科学研究项目(2015321) |
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| 摘 要： | 我国现阶段城市化的日益发展,使城市空气质量的宏观调控面临越来越大的压力。本文建立了关于空气质量的似乎不相关(SUR)模型,采用Jeffreys's的不变先验分析直接蒙特卡罗(DMC)方法,计算各参数的贝叶斯后验密度和未来值的预测密度。对中国厦门市区三项污染指标及四项外部驱动因素的数据进行实证分析,并将其与贝叶斯分层模型得出的结果进行比较。
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| 关 键 词： | 似乎不相关(SUR)模型 直接蒙特卡罗(DMC) 贝叶斯后验密度 城市空气质量 |
Urban Air Quality SUR Model Research Base on DMC Method |
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| QIAO Shan,XIE Sheng-lan,LIU Jin-shan,XIA Qiang.Urban Air Quality SUR Model Research Base on DMC Method[J].Application of Statistics and Management,2017(6):983-992. |
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| Authors: | QIAO Shan XIE Sheng-lan LIU Jin-shan XIA Qiang |
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| Abstract: | Urban air quality is subject to the increasing pressure of urbanization,This paper established a seemingly unrelated regression (SUR) model and adopt Markov chain Monte Carlo approach based on a direct Monte Carlo (DMC) methodology to analyze the air quality data on three pollutants and four external driving factors from urban district of Xiamen City,China.The results obtained by the DMC approach are compared with those yielded by Bayesian hierarchy model (BHM) developed by some authors for analysis of this air quality data. |
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| Keywords: | seemingly unrelated regressions direct Monte Carlo method Bayesian posterior density urban air quality |
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