

\subsection{\bf 5.6\hspace{1em} Robust Estimation--Motivation--I}

\begin{slide}
\begin{itemize}
\item See Andrews, et al. ``Robust Estimates of Location,'' Princeton
University Press; 

\item ``Robustness in Statistics,'' edited by R. L.
Laurer, G. N. Wilkinson, Academic Press (1979).

\item In the maximum likelihood method we found the method that had
the smallest possible Standard Deviation (asymptotically at least).

\item However, as we emphasized in the study of non-parametric estimates, it
is quite possible (and indeed probable) that systematic error from
{\em incorrect\/} theoretical form of probability is large.  

\item In many cases, one knows reasonably well the analytic form of the
``interesting'' effect but what one observes has other totally unknown
contributions.

\item One must choose between parameterizing the unknown or ignoring
known form of known effect.
\end{itemize}
\end{slide}

