| 摘要: |
| 基于《中国统计年鉴》最新数据，运用稀疏主成分方法及聚类分析方法，对2017年和2018年我国各地区城市建设水平的差异进行了研究；稀疏主成分分析在降维的同时，通过惩罚函数方法，对载荷矩阵进行稀疏化处理，其分析结果相较于主成分分析具有较强的可解释性；此外，对我国各地区进行了聚类分析，聚类结果验证了稀疏主成分法排名的合理性，结果表明：我国各地区城市建设水平是参差不齐的，江苏、浙江、广东、山东的城市建设水平较高，而西藏、宁夏、贵州的城市建设水平较低；最后，为我国各地区城市化的发展提供了一些对应的建议。 |
| 关键词: 稀疏主成分 聚类分析 城市建设 设施水平 |
| DOI： |
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| Research on the Level of Urban Construction in China |
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CHEN Yu-xin， LIU Hui-lan
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School of Mathematics and Statistics， Guizhou University， Guiyang 550025， China
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| Abstract: |
| Based on the latest data of China Statistical Yearbook， this paper uses sparse principal component and cluster analysis methods to study the difference of urban construction level in various regions of China in 2017 and 2018. Sparse principal component analysis uses a penalty function method to sparse the loading matrix while reducing the dimensionality of data， so that the analysis results are more interpretable than principal component analysis. Moreover， cluster analysis is carried out for each region in China， and the results verify the rationality of the ranking of the sparse principal component method. The results show that the level of urban construction in China is uneven, the level of urban construction in Jiangsu， Zhejiang， Guangdong and Shandong is higher than Tibet， Ningxia and Guizhou. Finally， some suggestions are provided for the development of urbanization in all parts of China. |
| Key words: sparse principal component cluster analysis urban construction facility level |
