  The optimal gain matrix of the Kalman filter is often derived by minimizing
the trace of the posterior covariance matrix. Here, I show that the Kalman gain
also minimizes the determinant of the covariance matrix, a quantity known as
the generalized variance. When the error distributions are Gaussian, the
differential entropy is also minimized.
