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污染数据线性回归模型的参数估计 被引量:3
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作者 钱伟民 翟健茹 《同济大学学报(自然科学版)》 EI CAS CSCD 北大核心 2003年第2期246-249,共4页
研究了简单回归模型中响应变量受到另一随机变量序列污染时 ,模型参数和污染系数的估计方法 .在适当条件下 。
关键词 污染数据线性回归模型 污染系数 参数估计 强相合性 污染比率 随机变量序列
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污染线性模型的相合估计 被引量:2
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作者 尹雅凌 《同济大学学报(自然科学版)》 EI CAS CSCD 北大核心 2001年第6期703-707,共5页
讨论二种类型的污染回归 .一是 (Ⅰ )型污染回归模型 ,并不假定误差分布为正态 ,也不假定误差方差为已知 ,只假定误差有三阶矩 ,在此条件下证明了污染系数及回归系数的参数估计的强相合性 ;二是提出一种新的污染回归模型 (Ⅲ ) ,在只假... 讨论二种类型的污染回归 .一是 (Ⅰ )型污染回归模型 ,并不假定误差分布为正态 ,也不假定误差方差为已知 ,只假定误差有三阶矩 ,在此条件下证明了污染系数及回归系数的参数估计的强相合性 ;二是提出一种新的污染回归模型 (Ⅲ ) ,在只假定误差有二阶矩 (并不假定有已知方差 )的条件下 ,得到污染系数及回归系数的参数估计的相合性 . 展开更多
关键词 污染系数 污染数据 相合估计 可识别条件 半参数回归模型 污染回归模型 参数估计
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Characteristics of ventilation coefficient and its impact on urban air pollution 被引量:1
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作者 路婵 邓启红 +2 位作者 刘蔚巍 黄柏良 石灵芝 《Journal of Central South University》 SCIE EI CAS 2012年第3期615-622,共8页
The temporal variation of ventilation coefficient was estimated and a simple model for the prediction of urban ventilation coefficient in Changsha was developed. Firstly, Pearson correlation analysis was used to inves... The temporal variation of ventilation coefficient was estimated and a simple model for the prediction of urban ventilation coefficient in Changsha was developed. Firstly, Pearson correlation analysis was used to investigate the relationship between meteorological parameters and mixing layer height during 2005-2009 in Changsha, China. Secondly, the multi-linear regression model between daytime and nighttime was adopted to predict the temporal ventilation coefficient. Thirdly, the validation of the model between the predicted and observed ventilation coefficient in 2010 was conducted. The results showed that ventilation coefficient significantly varied and remained high during daytime, while it stayed relatively constant and low during nighttime. In addition, the diurnal ventilation coefficient was distinctly negatively correlated with PM10 (particle with the diameter less than 10 μm) concentration in Changsha, China. The predicted ventilation coefficient agreed well with the observed values based on the multi-linear regression models during daytime and nighttime. The urban temporal ventilation coefficient could be accurately predicted by some simple meteorological parameters during daytime and nighttime. The ventilation coefficient played an important role in the PM10 concentration level. 展开更多
关键词 ventilation coefficient mixing layer height particulate matter multi-linear regression
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