tailieunhanh - Quantitative Methods and Applications in GIS - Chapter 7

Các thành phần chủ yếu, nhân tố, và phân tích cụm, và ứng dụng trong phân tích khu vực xã hội Chương này thảo luận về ba phương pháp phân tích đa biến quan trọng thống kê: thành phần chủ yếu phân tích (PCA), phân tích yếu tố (FA), và phân tích cluster (CA). PCA và FA thường được sử dụng với nhau để giảm dữ liệu bằng cách cơ cấu nhiều biến thành một số hạn chế của các thành phần (yếu tố). Các kỹ thuật này đặc biệt hữu ích để loại bỏ canh thẳng biến và phát hiện. | 7 Principal Components Factor and Cluster Analyses and Application in Social Area Analysis This chapter discusses three important multivariate statistical analysis methods principal components analysis PC A factor analysis FA and cluster analysis CA . PCA and FA are often used together for data reduction by structuring many variables into a limited number of components factors . The techniques are particularly useful for eliminating variable collinearity and uncovering latent variables. Applications of the methods are widely seen in socioeconomic studies also see case study 8 in Section . While the PCA and FA group variables the CA classifies many observations into categories according to similarity among their attributes. In other words given a dataset as a table the PCA and FA reduce the number of columns and the CA reduces the number of rows. Social area analysis is used to illustrate the techniques as it employs all three methods. The interpretation of social area analysis results also leads to a review and comparison of three classic models on urban structure namely the concentric zone model the sector model and the multinuclei model. The analysis demonstrates how analytical statistical methods synthesize descriptive models into one framework. Beijing the capital city of China on the verge of forming its social areas after decades under a socialist regime is chosen as the study area for a case study. Usage of GIS in this case study is limited to mapping for spatial patterns. Section discusses principal components and factor analysis. Section explains cluster analysis. Section reviews social area analysis. A case study on the social space in Beijing is presented in Section to provide a new perspective to the fast-changing urban structure in China. The chapter is concluded with a discussion and brief summary in Section . PRINCIPAL COMPONENTS AND FACTOR ANALYSIS Principal components and factor analysis are often used together for data .