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3 unusual facts about Robust regression


Robust regression

Robyn Dawes (1979) examined decision making in applied settings, showing that simple models with unit weights often outperformed human experts.

In fact, the type I error rate tends to be lower than the nominal level when outliers are present, and there is often a dramatic increase in the type II error rate.

Although it is sometimes claimed that least squares (or classical statistical methods in general) are robust, they are only robust in the sense that the type I error rate does not increase under violations of the model.



see also