FIX: ValueError LQMarkov convergence failed (#550)

* Fix: ValueError `LQMarkov` with beta>0.972 (#508)

* add line breaks to comply with pep8

* add docstring for max_iter parameter in LQMarkov

* move max_iter to kwarg of stationary_values, fix docstring, and indents for pep8

* edit line break for style consistency

quantecon/lqcontrol.py

@@ -479,7 +479,7 @@ def __str__(self):
  return dedent(m.format(b=self.beta, m=self.m, n=self.n, k=self.k,
  j=self.j, t=t))
 
- def stationary_values(self):
+ def stationary_values(self, max_iter=1000):
  """
  Computes the matrix :math:`P(s)` and scalar :math:`d(s)` that
  represent the value function
@@ -491,6 +491,11 @@ def stationary_values(self):
  in the infinite horizon case. Also computes the control matrix
  :math:`F` from :math:`u = - F(s) x`.
 
+ Parameters
+ ----------
+ max_iter : scalar(int), optional(default=1000)
+ The maximum number of iterations allowed
+
  Returns
  -------
  Ps : array_like(float)
@@ -512,7 +517,8 @@ def stationary_values(self):
  Qs, Rs, Ns = self.Qs, self.Rs, self.Ns
 
  # == Solve for P(s) by iterating discrete riccati system== #
- Ps = solve_discrete_riccati_system(Π, As, Bs, Cs, Qs, Rs, Ns, beta)
+ Ps = solve_discrete_riccati_system(Π, As, Bs, Cs, Qs, Rs, Ns, beta,
+ max_iter=max_iter)
 
  # == calculate F and d == #
  Fs = np.array([np.empty((k, n)) for i in range(m)])