In linear filtering theory, | = | v P| is called the innovation, and = PP + is the prediction error covariance.

In linear filtering theory, |η = | v − P|μ is called the innovation, and г = PΣP′ + Ω is the prediction error covariance. The quantity K = ∑P'T^-1 is called the Kalman-filter gain, and the Kalman-filter posterior moments are

Show that this formulation is equivalent to the Black– Litterman posterior moments (8.24) and (8.25) on page 152.

(8.24)

(8.25)