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] }, { "page": "extract_meta", "title": "extracts meta-variables indices", "topics": [ "extract_meta" ] }, { "page": "fun_lines", "title": "weighted sum/difference of two regression vectors", "topics": [ "fun_lines" ] }, { "page": "get_auc", "title": "Plot ROC curve and calculate AUC", "topics": [ "get_auc" ] }, { "page": "get_range_nclusters", "title": "compute range of number of clusters from ROC outputs take in parameter an object from reorder_mglasso_roc_calculations", "topics": [ "get_range_nclusters" ] }, { "page": "ggplot_roc", "title": "Title", "topics": [ "ggplot_roc" ] }, { "page": "graph_estimate", "title": "Neighborhood selection estimate", "topics": [ "graph_estimate" ] }, { "page": "image_sparse", "title": "Plot the image of a matrix", "topics": [ "image_sparse" ] }, { "page": "install_pylearn_parsimony", "title": "Install the python library pylearn-parsimony and other required libraries", "topics": [ "install_pylearn_parsimony" ] }, { "page": "lagrangian", "title": 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] }, { "page": "one_config", "title": "One simulation configuration", "topics": [ "one_config" ] }, { "page": "perf_one", "title": "compute TPR, FPR, SHD given estimated and true precision matrices", "topics": [ "perf_one" ] }, { "page": "perf_vec", "title": "get performances from list of estimations", "topics": [ "perf_vec" ] }, { "page": "plot_clusterpath", "title": "Plot MGLasso Clusterpath", "topics": [ "plot_clusterpath" ] }, { "page": "plot_mglasso", "title": "fonction qui affiche les matrices d'adjacence à chaque niveau de la hiérarchie à automatiser utiliser niveau de legende commune", "topics": [ "plot_mglasso" ] }, { "page": "precision_to_regression", "title": "Compute precision matrix from regression vectors", "topics": [ "precision_to_regression" ] }, { "page": "repart", "title": "pareil pour les clusters ACP dimensions ?", "topics": [ "repart" ] }, { "page": "select_ebic_weighted", "title": "EBIC", "topics": [ "select_ebic_weighted" ] }, { "page": "select_kfold", "title": 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