Why Linear Models Can Still Work in a Complex and Changing World
Linear models can perform well in complex environments when instability is primarily nonlinear. This occurs because linear models omit unstable curvature, leading to fewer prediction errors in new settings compared to flexible models that exploit environmental-specific complexities. The choice between linear and nonlinear complexity depends on the stability of those rules across different conditions.