Abstract
The study provides an observed probability measurement of urbanization level with errors-in-variables observation, which is an innovative nonparametric kernel density approach. The probability changes are observed through the impacts of factors (population and GDP). First, the urbanization process in China can be divided into four stages under the impacts of factors: the observed probability of urbanization level decreases with the impact of each factor at the early stage of urbanization process; while the observed probability increases with the impact of each factor at the middle stage; the observed probabilities at both transition stage and late stage show slight changes under the impact of each factor. Secondly, the observed probability measurement method is also applied to investigate the urbanization development in eastern China, illustrating its general application. Finally, GDP plays a greater role on promoting urbanization development than population. ICIC International
Original language | English |
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Pages (from-to) | 1233-1242 |
Number of pages | 10 |
Journal | International Journal of Innovative Computing, Information and Control |
Volume | 4 |
Issue number | 5 |
Publication status | Published - 2008 May |
Keywords
- Errors-in-variables
- Measurement
- Urbanization level
- Weighted kernel density estimation
ASJC Scopus subject areas
- Computational Theory and Mathematics
- Information Systems
- Software
- Theoretical Computer Science