components do not depend on the parameters $\mu^j$, (see [@Sat94; @BSD96] for details) we can choose a new set of parameters in which the covariance matrix is diagonal. The transformation can be affected by means of an orthogonal transformation. We have the new parameter set $\bbox{\nu}\equiv\{A,\nu^1,\nu^2,\nu^3\}$, related to $\bbox{\mu}$ by means of the relation $\bbox{\nu}={\bf S}
\bbox{\mu}$, where $\bf S$ is a orthogonal matrix, which for our particular case is: $$\label{smat}
{\bf S} = \left(\begin{tabular}{cccc}
$1.0$&0.0&0.0&0.0\\
0.0\ \ &-0.794  & 0.129 &  -0.594\\
0.0&0.359&  -0.690 & -0.629\\
0.0&-0.491 &  -0.713 & 0.501\\
\end{tabular}\right)$$ In this new coordinate system the covariance matrix ${\bf C}_{(\nu)} =
{\bf S}{\bf C}_{(\mu)}{\bf S^{-1}}$, and is given by, $$\label{cov2}
{\bf C}_{(\bbox{\nu})} = \frac{1}{{\check A}^2}\left(\begin{tabular}{cccc}
${\check  A}^2$&0.0&0.0&0.0\\
0.0\ \ &0.024&0.0&0.0\\
0.0&0.0&1.640&0.0\\
0.0&0.0&0.0&922.3\\
\end{tabular}\right)$$ In the high SNR limit the root mean square errors in the parameters $\nu^a$ are given by, $$\sigma_{\nu^a} = \sqrt{C^{aa}}.$$ For an SNR of $10$ the values are $\{1.0,\ 0.015,\ 0.128,\ 3.037\}$.

In a previous work [@BSD96] we had performed detailed Monte Carlo simulations to study the variation of the errors with the SNR. The simulations carried out in that paper were with a slightly different power spectrum, as we have used a simple 