Regression model
稳健因子分析
稳健因子分析在抵抗异常值干扰的同时，恢复多元连续数据的潜在因子结构。该方法由 Pison, Rousseeuw, Filzmoser 和 Croux (2003) 提出，它在提取因子之前，用诸如最小协方差行列式 (MCD) 或 S-估计量等稳健估计量替换经典的样本协方差。
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Method map
The neighbourhood of related methods — select a node to explore.
来源
- Pison, G., Rousseeuw, P. J., Filzmoser, P., & Croux, C. (2003). Robust factor analysis. Journal of Multivariate Analysis, 84(1), 145-172. DOI: 10.1016/S0047-259X(02)00007-6 ↗
- 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 Factor Analysis. ScholarGate. https://scholargate.app/zh/statistics/robust-factor-analysis
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- 因子分析研究统计学↔ compare
- 影响诊断 (库克距离, DFFITS, 杠杆率)统计学↔ compare
- 主成分分析机器学习↔ compare
- 稳健协方差估计 (MCD)统计学↔ compare
- 鲁棒主成分分析 (RPCA)统计学↔ compare