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  pdftitle={Analyzing the capacity of the colBiSBM to recover structure for missing data from other networks},
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\title{Analyzing the capacity of the colBiSBM to recover structure for
missing data from other networks}
\author{}
\date{\vspace{-2.5em}}

\begin{document}
\maketitle

\begin{verbatim}
## `summarise()` has grouped output by 'prop_NAs'. You can override using the
## `.groups` argument.
\end{verbatim}

\hypertarget{simulation-context}{%
\section{Simulation context}\label{simulation-context}}

The idea is to benchmark the capacity of the models when NAs are in the
data.

To do this, whe choose the below structure: ! PARAMETERS OF THE
SIMULATION !

And set some randomly chosen interactions to NA. The below plots will
show the different quality indicators in function of proportion of NAs
in the first of the 3 networks.

\hypertarget{auc-in-function-of-the-proportion-of-nas}{%
\section{AUC in function of the proportion of
NAs}\label{auc-in-function-of-the-proportion-of-nas}}

\includegraphics{NA_robustness_analyse_files/figure-latex/auc_plots-1.pdf}

\hypertarget{ari-in-function-of-the-proportion-of-nas}{%
\section{ARI in function of the proportion of
NAs}\label{ari-in-function-of-the-proportion-of-nas}}

\begin{figure}
\centering
\includegraphics{NA_robustness_analyse_files/figure-latex/ARI_row_plot-1.pdf}
\caption{Difference of ARI for the row clusterings}
\end{figure}

\begin{figure}
\centering
\includegraphics{NA_robustness_analyse_files/figure-latex/ARI_col_plot-1.pdf}
\caption{Difference of ARI for the columns clusterings}
\end{figure}

\end{document}
