Latent structureMultivariate analysis
贝叶斯主成分分析 (BPCA)
贝叶斯主成分分析将概率主成分分析嵌入贝叶斯框架中，为载荷矩阵设置先验，从而自动剔除不相关的成分。它能自然地处理缺失数据，并为潜在得分和表示的维度提供基于原理的不确定性估计。
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Method map
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来源
- Bishop, C. M. (1999). Bayesian PCA. In M. S. Kearns, S. A. Solla & D. A. Cohn (Eds.), Advances in Neural Information Processing Systems 11 (pp. 382–388). MIT Press. link ↗
- Tipping, M. E. & Bishop, C. M. (1999). Probabilistic principal component analysis. Journal of the Royal Statistical Society: Series B, 61(3), 611–622. DOI: 10.1111/1467-9868.00196 ↗
如何引用本页
ScholarGate. (2026, June 3). Bayesian Principal Component Analysis. ScholarGate. https://scholargate.app/zh/statistics/bayesian-principal-component-analysis
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