I have some problems understanding these parts of the course/exercises
1) In series 12, why is the density of y_j, g(y_j-x_j^T beta), where g() is the denstiy of epsilon_j, my guess would be that y_j-x_j^T beta = epsilon_j but then why do they have different density functions ? Or are they actually the same "modulo a shift" ?
2)On the slides about Robust/Resistent Regression: M-estimation as Weighted Regression : when taking the derivative with respect to gamma, why is there still x_i^T in the sum with psi, since according to the chain rule we take the transpose of x_i^T ?
Thanks in advance.