'(array) The variance / covariance matrix. Computed using the numerical
Hessian approximated by complex step or finite differences methods.'

@cache_readonly
def cov_params_approx(self):

    evaluated_hessian = self.model.hessian(self.params, transformed=True)
    (neg_cov, singular_values) = pinv_extended(evaluated_hessian)
    if (self._rank is None):
        self._rank = np.linalg.matrix_rank(np.diag(singular_values))
    return (- neg_cov)
