Estimating equations for L1 loss 4. (10 points) In lecture, we derived the estimating equations for SLR, which we obtained by differentiating the mean squared error with respect to a and b. Now, suppose that we choose the same model, y = a + bxi, but we minimize the LI loss instead. That is, we minimize the mean absolute error, defined as MAE(a, b) = n Elyi - a - bail. (a) (2 points) Show that the partial derivatives of lyi - a - bx;| with respect to a and b are a da -yi - a - bxil = -sgn(yi - a - bxi) ab yi - a - bxil = -xi . sgn(yi - a - bxi), and undefined if yi - a + bxi, where sgn is the sign function defined by +1 if z > 0 sgn (z = -1 if z