Covariance matrix of theta. This is estimated by the inverse hessian
of the log likelihood function.
theta : array of shape = (n*(n-1)/2 + n)
The free parameters of the model at the MLE. These values are the
linearized elements of the upper triangular portion of the symmetric
rate matrix, S, followed by the log of the equilibrium distribution.
n : int
The size of counts
Returns:
sigma_eigenvalues : array, shape=(n,)
Estimate of the element-wise asymptotic standard deviation of the
eigenvalues of the rate matrix (in sorted order).