'Create a generator to calculate the population mean and
variance-convariance matrix for both :math:`x_t` and :math:`y_t`
starting at the initial condition (self.mu_0, self.Sigma_0).
Each iteration produces a 4-tuple of items (mu_x, mu_y, Sigma_x,
Sigma_y) for the next period.
Yields
mu_x : array_like(float)
An n x 1 array representing the population mean of x_t
mu_y : array_like(float)
A  k x 1 array representing the population mean of y_t
Sigma_x : array_like(float)
An n x n array representing the variance-covariance matrix
of x_t
Sigma_y : array_like(float)
A k x k array representing the variance-covariance matrix
of y_t'

def moment_sequence(self):

    (A, C, G, H) = (self.A, self.C, self.G, self.H)
    (mu_x, Sigma_x) = (self.mu_0, self.Sigma_0)
    while 1:
        mu_y = G.dot(mu_x)
        if (H is None):
            Sigma_y = G.dot(Sigma_x).dot(G.T)
        else:
            Sigma_y = (G.dot(Sigma_x).dot(G.T) + H.dot(H.T))
        (yield (mu_x, mu_y, Sigma_x, Sigma_y))
        mu_x = A.dot(mu_x)
        Sigma_x = (A.dot(Sigma_x).dot(A.T) + C.dot(C.T))
