'Returns
W: array of eigenvectors
eigva: list of eigenvalues
k: matrix indicating column # of largest eigenvalue for each c_i,j'

def _eigval_decomp_SZ(self, irf_resim):

    neqs = self.neqs
    periods = self.periods
    cov_hold = np.zeros((neqs, neqs, periods, periods))
    for i in range(neqs):
        for j in range(neqs):
            cov_hold[i, j, :, :] = np.cov(irf_resim[:, 1:, i, j], rowvar=0)
    W = np.zeros((neqs, neqs, periods, periods))
    eigva = np.zeros((neqs, neqs, periods, 1))
    k = np.zeros((neqs, neqs))
    for i in range(neqs):
        for j in range(neqs):
            (W[i, j, :, :], eigva[i, j, :, 0], k[(i, j)]) = util.eigval_decomp(cov_hold[i, j, :, :])
    return (W, eigva, k)
