Latent structure
典型相关分析
典型相关分析（CCA）是一种多元统计方法，它识别两个变量集中的线性组合对——每个变量集一个——使得每对组合之间的相关性最大化。CCA由Harold Hotelling在其1936年发表于Biometrika的开创性论文中提出，它为研究两个多元测量组之间的关联提供了最通用的线性框架，许多经典方法（如多元回归、MANOVA、判别分析）都是它的特例。
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来源
- Hotelling, H. (1936). Relations between two sets of variates. Biometrika, 28(3–4), 321–377. DOI: 10.1093/biomet/28.3-4.321 ↗
- Anderson, T. W. (2003). An Introduction to Multivariate Statistical Analysis (3rd ed.). Wiley. ISBN: 978-0471360919
- Tabachnick, B. G., & Fidell, L. S. (2019). Using Multivariate Statistics (7th ed.). Pearson. ISBN: 978-0134790541
如何引用本页
ScholarGate. (2026, June 3). Canonical Correlation Analysis. ScholarGate. https://scholargate.app/zh/statistics/canonical-correlation-analysis
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