Q2. Suppose that time series {X} is an AR(1) process Xt = axt-1 Wt, where 0...

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Q2. Suppose that time series {X} is an AR(1) process Xt = axt-1 Wt, where 0 < a <1 and W is normalized standard white noise with Wt ~ N(0, 1). If we have observed X1 and X3, and we would like to estimate the missing value X2. Find the best linear predictor of X2, given X1 and X3. Q2. Suppose that time series {X} is an AR(1) process Xt = axt-1 Wt, where 0 < a <1 and W is normalized standard white noise with Wt ~ N(0, 1). If we have observed X1 and X3, and we would like to estimate the missing value X2. Find the best linear predictor of X2, given X1 and X3.