Regression model
稳健判别分析
稳健判别分析是一种分类方法，它使用线性判别函数分离各组，同时抵抗异常值的影响。它用高崩溃估计量（如最小协方差行列式（MCD））替换经典的均值和协方差，这是Hawkins & McLachlan (1997) 和 Croux & Dehon (2001) 开发的一种方法。
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Method map
The neighbourhood of related methods — select a node to explore.
来源
- Hawkins, D. M. & McLachlan, G. J. (1997). High Breakdown Linear Discriminant Analysis. Journal of the American Statistical Association, 92(437), 136-143. DOI: 10.1080/01621459.1997.10473610 ↗
- Croux, C. & Dehon, C. (2001). Robust Linear Discriminant Analysis Using S-Estimators. Canadian Journal of Statistics, 29(3), 473-493. DOI: 10.2307/3316042 ↗
如何引用本页
ScholarGate. (2026, June 1). High-Breakdown Robust Linear Discriminant Analysis. ScholarGate. https://scholargate.app/zh/statistics/robust-discriminant-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.
- 异方差稳健 (HC) 标准误统计学↔ compare
- 线性判别分析 (LDA)机器学习↔ compare
- 逻辑回归研究统计学↔ compare
- 二次判别分析 (QDA)机器学习↔ compare
- 稳健逻辑回归统计学↔ compare