def estimator_cov(self,method):
""" Creates covariance matrix for the estimators
Parameters
----------
method : str
Estimation method
Returns
----------
A Covariance Matrix
"""
Y = np.array([reg[self.lags:] for reg in self.data])
Z = self._create_Z(Y)
if method == 'OLS':
sigma = self.ols_covariance()
else:
sigma = self.custom_covariance(self.latent_variables.get_z_values())
return np.kron(np.linalg.inv(np.dot(Z,np.transpose(Z))), sigma)
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