update QuantEcon.py QuantEcon/QuantEcon.py#569

Author: mmcky

lectures/linear_models.md

@@ -734,7 +734,7 @@ sample_size = 500_000
 ar = LinearStateSpace(A_2, C_2, G_2, mu_0=np.ones(4))
 fig, ax = plt.subplots()
 x, y = ar.simulate(sample_size)
-mu_x, mu_y, Sigma_x, Sigma_y = ar.stationary_distributions()
+mu_x, mu_y, Sigma_x, Sigma_y, Sigma_yx = ar.stationary_distributions()
 f_y = norm(loc=float(mu_y), scale=float(np.sqrt(Sigma_y)))
 y = y.flatten()
 ygrid = np.linspace(ymin, ymax, 150)
@@ -920,7 +920,7 @@ def cross_plot(A,
     ar = LinearStateSpace(A, C, G, mu_0=np.ones(4))
 
     if steady_state == 'True':
-        μ_x, μ_y, Σ_x, Σ_y = ar.stationary_distributions()
+        μ_x, μ_y, Σ_x, Σ_y, Σ_yx = ar.stationary_distributions()
         ar_state = LinearStateSpace(A, C, G, mu_0=μ_x, Sigma_0=Σ_x)
 
     ymin, ymax = -0.6, 0.6

lectures/perm_income_cons.md

@@ -345,7 +345,7 @@ G = np.array([[0., 1., 0.]])
 μ_z0 = np.array([[1.0], [0.0], [0.0]])
 Σ_z0 = np.zeros((3, 3))
 Lz = qe.LinearStateSpace(A, C, G, mu_0=μ_z0, Sigma_0=Σ_z0)
-μ_z, μ_y, Σ_z, Σ_y = Lz.stationary_distributions()
+μ_z, μ_y, Σ_z, Σ_y, Σ_yx = Lz.stationary_distributions()
 
 # Mean vector of state for the savings problem
 mxo = np.vstack([μ_z, 0.0])

lectures/samuelson.md

@@ -1316,7 +1316,7 @@ class SamuelsonLSS(LinearStateSpace):
         # values for simulation
         if stationary == True:
             try:
-                self.μ_x, self.μ_y, self.σ_x, self.σ_y = \
+                self.μ_x, self.μ_y, self.σ_x, self.σ_y, self.σ_yx = \
                     self.stationary_distributions()
                 self.μ_0 = self.μ_y
                 self.Σ_0 = self.σ_y