Estimating spatial logistic model: A deterministic approach or a heuristic approach?
Publication in refereed journal

香港中文大學研究人員

引用次數
替代計量分析
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摘要This paper evaluates the performance of a deterministic method (Newton-Raphson, NR) and a heuristic method (Genetic Algorithm, GA) for solving the maximum likelihood estimation in spatial logistic analysis. A spatial logistic regression model equipped with a filtering process is formulated to examine the relationship between land use change and various spatial determinants such as population density, distance to road, distance to commercial center and neighborhood characteristics. Geographic Information System (GIS) is used to acquire spatial samples and perform spatial analysis. The NR method and GA are utilized, respectively, to estimate the coefficients that maximize the likelihood of the spatial logistic regression model. Both methods are compared in terms of the maximum likelihood and computing time. The experimental results show that the NR method can achieve a better likelihood and is also much faster than the GA method. Therefore, the NR method is recommended for estimating a spatial logistic regression model although GA can also be employed. (C) 2015 Elsevier Inc. All rights reserved.
著者Zhang XX, Huang B, Tay R
期刊名稱Information Sciences,Information Sciences
出版年份2016
月份2
日期10
卷號330
出版社ELSEVIER SCIENCE INC
頁次358 - 369
國際標準期刊號0020-0255
電子國際標準期刊號1872-6291
語言英式英語
關鍵詞genetic algorithm; land use; Logistic regression model; Newton-Raphson method; spatial sampling and filtering
Web of Science 學科類別Computer Science; Computer Science, Information Systems

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