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1.10 Suppose we would like to predict a single stationary series x, with zero mean and autocorrelation function y(h) at some time in the future, say, t + 6, for ( > 0. (a) If we predict using only x, and some scale multiplier A, show that the mean-square prediction error MSE(A) = E[(Xte - Axt )21 is minimized by the value A = p(C). (b) Show that the minimum mean-square prediction error is MSE(A) = Y(0)[1 - p2(0)]. (c) Show that if Xtte = Axt, then p(() = 1 if A > 0, and p(() = -1 if A