Abstract
Canonical correlation analysis (CCA) has the ability to deal with two sets of multivariate variables simultaneously and to produce both structural and spatial meanings. In view of the valuable insights to be gained, in this paper I examine the potential applications of CCA in regional science by describing its algorithm in a regional or spatial context. Next, I apply CCA to explore the mutually interdependent relationship between transport and development inChina's Zhujiang Delta. The results highlight the utility of CCA in revealing the structural and spatial patterns of two dominant and four subdominant transport‐development relationships in this growing region of China.
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