ggmModSelect.Rnw

\documentclass{article}

\usepackage[
    paperwidth=27cm,paperheight=13cm,
    margin=1cm,
    ]{geometry}
    
\usepackage{amsmath}
\usepackage{amsfonts}
\usepackage{amssymb}

\usepackage[latin1]{inputenc}
\usepackage{tikz}
\usetikzlibrary{shapes,arrows}
\usetikzlibrary{arrows.meta}
\usetikzlibrary{calc}
\begin{document}
\pagestyle{empty}


% Define block styles
\tikzstyle{decision} = [diamond, draw, fill=gray!20, 
    text width=5em, text badly centered, node distance=3cm, inner sep=0pt]
    
\tikzstyle{start} = [rectangle, draw, fill=white, 
    text width=20em, text centered, rounded corners, minimum height=4em]
    
    
\tikzstyle{block} = [rectangle, draw, fill=gray!20, 
    text width=20em, text centered, rounded corners, minimum height=4em]
    
\tikzstyle{smallblock} = [rectangle, draw, fill=gray!20, 
    text width=10em, text centered, rounded corners, minimum height=4em]
    
% \tikzstyle{line} = [draw, -latex']
\tikzstyle{line} = [draw, -{Latex[length=2mm, width=1.5mm]}]

\tikzstyle{cloud} = [draw, ellipse,fill=white, node distance=3cm,
    minimum height=3em]
    
\begin{tikzpicture}[node distance = 2cm, auto]
    % Place nodes

    \node [block] (prune) {3. Compute the BIC for each model estimated in 2, and set the model with the lowest BIC to $\mathcal{M}^{\mathrm{cur}}$};
        
 
    
  
  \node [block, below of = prune, node distance=2.5cm] (edgelist) {4. Form a list $\mathcal{E}^{\mathrm{full}}$ that includes all included possible edges (both present and absent edges in $\mathcal{M}^{\mathrm{cur}}$)};
  
    % \node [decision, below of = edgelist] (isempty) {is $\mathcal{E}^{\mathrm{full}}$ empty?};
    
        \node [below of = edgelist, node distance=3cm] (isempty) {};
    
    % Stop1:
    \node [cloud, right of = isempty, node distance=6cm] (stop1) {Return $\mathcal{M}^{\mathrm{cur}}$};
    
    \node [smallblock, below of = isempty, node distance=2cm] (setcur) {5. Set $\mathcal{E}^{\mathrm{sub}} \leftarrow \mathcal{E}^{\mathrm{full}}$};
    
   \node [block, right of = setcur, node distance=10cm] (fitproposals) {6. For each edge $i$ listed in $\mathcal{E}^{\mathrm{sub}}$, fit a proposal model $\mathcal{M}^{\mathrm{prop}}_i$ in which edge $i$ is included or removed in $\mathcal{M}^{\mathrm{cur}}$};
   

   
   
    \node [decision, above of = fitproposals] (anyBIC) {Any $\mathcal{M}^{\mathrm{prop}}_i$ with lower BIC than $\mathcal{M}^{\mathrm{cur}}$?};
    
    
      \node [decision, above of = stop1, node distance=3cm] (setsequal) {$\mathcal{E}^{\mathrm{full}} = \mathcal{E}^{\mathrm{sub}}$?};

    \node [block, right of = setsequal, node distance=11cm] (cleanset) {7. For every edge $i$, remove $i$ from $\mathcal{E}^{\mathrm{sub}}$ if the BIC of $\mathcal{M}^{\mathrm{prop}}_i$ is higher than the BIC of $\mathcal{M}^{\mathrm{cur}}$.};
    
    
        \node [block] at (anyBIC -| cleanset) (updateModel) {8. With $j$ representing the added/removed edge that reduced BIC the most, set $\mathcal{M}^{\mathrm{cur}} \leftarrow \mathcal{M}^{\mathrm{prop}}_j$ and remove $j$ from $\mathcal{E}^{\mathrm{sub}}$.};

\node [decision] at (fitproposals -| updateModel) (setempty) {Is $\mathcal{E}^{\mathrm{sub}}$ empty?};

  
        \node [start] at (prune -| cleanset) (init) {1. Use \emph{glasso} to estimate $100$ regularized network models, ranging from sparse to dense};
        
            \node [block] at ($(prune)!0.5!(init)$) (init2) {2. For each of these models, fit an unregularized network using \emph{glasso} without regularization but with zeroes constrained according to the network structure};
    
      \node  at (0, 1.25) {ggmModSelect algorithm};
    
    % Edges
    \path [line] (init) -- (init2);
    
     \path [line] (init2) -- (prune);
    
    \path [line] (prune) -- (edgelist);
    
    \path [line] (edgelist) -- (setcur);
    
    % \path [line] (isempty) -- node {yes} (stop1);
    
    % \path [line] (isempty) -- node {no} (setcur);
    
     \path [line] (setcur) -- (fitproposals);
     
      \path [line] (fitproposals) -- (anyBIC);
     
      \path [line] (anyBIC) -- node {no} (setsequal);
    
    \path [line] (setsequal) -- node {yes} (stop1);
          
    \path [line] (setsequal) -- node {no} (edgelist);
    
    \path [line] (anyBIC) |- node {yes} (cleanset);
    
     \path [line] (updateModel) -- (setempty);
     
          \path [line] (cleanset) -- (updateModel);
     
     \path [line] (setempty) -- node {no} (fitproposals);
     
     
      % \path [line] (setempty) |- node {yes} (-3,-10) -- (-3, -3.45);
      
      
       \path [line] (setempty) |- node [near start] {yes} (0,-9.25) -| (-3, -3.25);
    % \node [block] (init) {initialize model};
    % \node [cloud, right of=init] (expert) {expert};
    % \node [cloud, right of=init] (system) {system};
    % \node [block, below of=init] (identify) {identify candidate models};
    % \node [block, below of=identify] (evaluate) {evaluate candidate models};
    % \node [block, right of=evaluate, node distance=3cm] (update) {update model};
    % \node [decision, below of=evaluate] (decide) {is best candidate better?};
    % \node [block, below of=decide, node distance=3cm] (stop) {stop};
    % % Draw edges
    % \path [line] (init) -- (identify);
    % \path [line] (identify) -- (evaluate);
    % \path [line] (evaluate) -- (decide);
    % \path [line] (decide) -| node [near start] {yes} (update);
    % \path [line] (update) |- (identify);
    % \path [line] (decide) -- node {no}(stop);
    % \path [line,dashed] (expert) -- (init);
    % \path [line,dashed] (system) -- (init);
    % \path [line,dashed] (system) |- (evaluate);
\end{tikzpicture}


\end{document}