Observed probability measurement for urbanization development level with errrors-in-variables observation

Bing Xu, Junzo Watada

    Research output: Contribution to journalArticle

    7 Citations (Scopus)

    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 languageEnglish
    Pages (from-to)1233-1242
    Number of pages10
    JournalInternational Journal of Innovative Computing, Information and Control
    Volume4
    Issue number5
    Publication statusPublished - 2008 May

    Fingerprint

    China
    Kernel Density
    Errors in Variables
    Observation
    Decrease

    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

    Cite this

    Observed probability measurement for urbanization development level with errrors-in-variables observation. / Xu, Bing; Watada, Junzo.

    In: International Journal of Innovative Computing, Information and Control, Vol. 4, No. 5, 05.2008, p. 1233-1242.

    Research output: Contribution to journalArticle

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