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\emph{\fontshape{sc} Abstract}
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The purpose of this document is to present the OpenTURNS-Mixmod module, which enables to build mixtures of multidimensional Normal distributions from a multidimensional sample. This construction is done with a control over the number of atoms in the mixture and over the covariance structure of these atoms. Some capabilities to perform classification are also provided.

This document is organised according to the Open TURNS documentation :
\begin{itemize}
\item a \itshape{Reference Guide} which gives some theoretical basis on bayseian networks,
\item a \itshape{Use cases Guide} which details scripts in python (the Textual Interface langage of Open TURNS) and helps the User to learn as quickly as possible the manipulation of the $otmixmod$ module,
\item the \itshape{User Manual} which details the $otmixmod$ objects and give the list of their methods,
\item the \itshape{Examples Guide} which provides at the moment only one example performed with the  $otmixmod$ module.
\end{itemize}

