Denote data point as (xi , yi), xi R p , i = 1, . . . , n. Given a Gaussian kernel function Kh(z) = 1 ( 2h) p e 2 z h 2 2 , z R p . Local linear regression solves 0 R, 1 R p , for a given predictor x R p : b := (b0, b1) = arg min nX i=1 (yi 0 (x x i ) T 1) 2Kh(x xi) (a) (10 points) Show that the solution is given in the form b = (XT W X) 1XT W Y