Continuing Example 9.10, the 21-dimensional vector X has correlation matrix RX with i, jth element
We use the observation vector Y = Y(n) = [Y1 ··· Yn]' to estimate X = X21. Find the LMSE estimate 
L (Y(n)) = 
(n)Y(n). Graph the mean square error e∗L(n) as a function of the number of observations n for φ0 ∈ {0.1, 0.5, 0.9}. Interpret your results. Does smaller φ0 or larger φ0 yield better estimates?
Example 9.10
The correlation matrix RX of a 21-dimensional random vector X has i, jth element
W is a random vector, independent of X, with expected value E[W] = 0 and diagonal correlation matrix RW = (0.1) I. Use the first n elements of Y = X+W to form a linear estimate of X21 and plot the mean square error of the optimum linear estimate as a function of n for
