Regression model
鲁棒主成分分析 (RPCA)
鲁棒主成分分析是一种降维方法，可在数据受到异常值和噪声污染时提取可靠的成分。该方法由 Candès、Li、Ma 和 Wright (2011) 提出，并在 Hubert、Rousseeuw 和 Vanden Branden (2005) 的 ROBPCA 方法中得到发展，它将数据矩阵分解为一个干净的低秩部分和一个稀疏的异常值部分。
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来源
- Candès, E. J., Li, X., Ma, Y., & Wright, J. (2011). Robust Principal Component Analysis? Journal of the ACM, 58(3), 1-37. DOI: 10.1145/1970392.1970395 ↗
- Hubert, M., Rousseeuw, P. J., & Vanden Branden, K. (2005). ROBPCA: A New Approach to Robust Principal Component Analysis. Technometrics, 47(1), 64-79. DOI: 10.1198/004017004000000563 ↗
如何引用本页
ScholarGate. (2026, June 1). Robust Principal Component Analysis. ScholarGate. https://scholargate.app/zh/statistics/robust-pca
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