Regression model
Robust Discriminant Analysis
Robust Discriminant Analysis is a classification method that separates groups with a linear discriminant function while resisting the influence of outliers. It replaces the classical mean and covariance with a high-breakdown estimator such as the Minimum Covariance Determinant (MCD), an approach developed by Hawkins & McLachlan (1997) and Croux & Dehon (2001).
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Sources
- 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 ↗