西安市空气质量影响因素的分位数回归分析

空气质量无论对经济的发展还是人体的健康都尤为重要。以大气中PM2.5浓度的变化为研究对象,采用逐步回归的方法对PM2.5影响最严重和最显著的因素进行筛选,利用这些因素构建普通多元线性回归模型和线性分位数回归模型来研究PM2.5浓度,全面细致地探究气象因素和污染物排放因素对西安市PM2.5浓度的影响,分析了普通多元线性回归模型和线性分位数回归模型不同分位点自变量对因变量的影响大小以及显著性特点,得出影响因素在不同分位点上的变化趋势。

Quantile Regression Analysis of Influencing Factors of Air Quality in Xi''an

Air quality is particularly important for both economic development and human health.With the change of PM2.5 concentration in the atmosphere, the gradual regression was used to screen the most serious and most significant factors of PM2.5. These factors are constructed ordinary multiple linear regression model and linear quantile regression model to study PM2.5 concentration, the influence of meteorological factors and pollutant emission factors on PM2.5 concentration in Xi''an are explored, the influence size and significance characteristics of different multiple linear regression model and linear quantile regression model are analyzed, and the change trend of influencing factors at different loci is obtained.