

\subsection{\bf Experience with Marquardt's Method}

\begin{slide}
\begin{itemize}
\item I have used both successfully.

\item I used Marquardt's method in the analysis of some $10^6$ Fermilab
events where on each event, I fitted known shower slopes to measured
photon energy measurements in a segmented lead-scintillator sandwich.

\item Here $n\sim 10$ and the large number of fits $(10^6)$ required a
fast method.

\item In these million fits, I saw no problem with divergence.

\item This is case where it was necessary to find a fast reliable
method.

\item I used the eigenvalue method in analysis of experimental data in
terms of theoretical models.

\item Here, one is typically only doing a few (maybe one) fit and so
speed of minimizer is irrelevant.
\end{itemize}
\end{slide}

