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% CHOOSE ONE TOPIC BY REMOVING THE SIGN % IN FRONT OF IT

%\noindent {\it Classical mathematical analysis,  inequalities, convexity}
%\noindent{\it   Graph theory and Combinatorics}
%\noindent{\it  Special functions}
%\noindent{\it Differential equations}
%\noindent{\it  Functional analysis}
%\noindent{\it Numerical analysis}
%\noindent{\it  Complex analysis}
%\noindent{\it  Probability and Statistics}
%\noindent{\it Mathematical aspects of computer science}
%\noindent{\it  Differential geometry and related topics}
%\noindent{\it   Number theory}
%\noindent{\it  Applications of mathematics in Electrical Engineering and Telecommunications}
\hfill % INDICATE IF YOUR WORK WILL BE PRESENTED AS A TALK OR AS A POSTER,
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%{\it Talk}
%{\it Poster}


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{\bf THE TITLE OF THE TALK OR POSTER (CAPITAL LETTERS)}

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\noindent
{\small{\sc Beatriz Vaz de Melo Mendes }\\[1mm]
Instituto de Matem\'atika, Universidade Federal do Rio de Janeiro,
Rio de Janeiro, Brazil. Email: {\sf xxx@yyy.zzz.br\\[2mm]}} % IF THERE IS NO SECOND AUTHOR, PLEASE DELETE BELOW.
{\small{\sc Milan Merkle}\\[1mm]
Faculty of Electrical Engineering, University of Belgrade,
11120 Belgrade, Serbia and Montenegro. Email: {\sf emerkle@etf.bg.ac.yu}}

\vspace{1cc} %PLACE HERE THE TEXT OF YOUR ABSTRACT.
{\small We give an equivalent definition of {\sc Pitman}'s closeness criterion
[{\bf 1}], in terms of medians of the difference of loss functions. Based on that definition,
we present some relations between {\sc Pitman}'s closeness and usual decision theoretical framework, then a result which enables comparison of estimators with a presence of a
positive or negative association, and a {\sc Rao-Blackwell} type result related to improving estimators by a conditioning.
}

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{\small\bf REFERENCES}

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\item {\small {\sc E. Pitman:} {\it The ``closest'' estimates of statistical parameters}.
Proc. Cambridge Phil. Soc., {\bf 33} (1937), 212--222.}
\end{list}


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