| addRowToTau | split group q of provided tau randomly into two into |
| ARI | Evalute the adjusted Rand index |
| classInd | convert a clustering into a 0-1-matrix |
| convertGroupPair | transform a pair of block identifiers (q,l) into an identifying integer |
| convertGroupPairIdentifier | takes a scalar indice of a group pair (q,l) and returns the values q and l |
| convertNodePair | transform a pair of nodes (i,j) into an identifying integer |
| correctTau | corrects values of the variational parameters tau that are too close to the 0 or 1 |
| emv_gamma | compute the MLE in the Gamma model using the Newton-Raphson method |
| fitNSBM | VEM algorithm to adjust the noisy stochastic block model to an observed dense adjacency matrix |
| getBestQ | optimal number of SBM blocks |
| getRho | compute rho associated with given values of w, nu0 and nu |
| getTauql | Evaluate tau_q*tau_l in the noisy stochastic block model |
| graphInference | new graph inference procedure |
| ICL_Q | computation of the Integrated Classification Likelihood criterion |
| initialPoints | compute a list of initial points for the VEM algorithm |
| initialPointsByMerge | Construct initial values with Q groups by meging groups of a solution obtained with Q+1 groups |
| initialPointsBySplit | Construct initial values with Q groups by splitting groups of a solution obtained with Q-1 groups |
| initialRho | compute initial values of rho |
| initialTau | compute intial values for tau |
| J.gamma | evaluate the objective in the Gamma model |
| JEvalMstep | evaluation of the objective in the Gauss model |
| listNodePairs | returns a list of all possible node pairs (i,j) |
| lvaluesNSBM | compute conditional l-values in the noisy stochastic block model |
| mainVEM_Q | main function of VEM algorithm with fixed number of SBM blocks |
| mainVEM_Q_par | main function of VEM algorithm for fixed number of latent blocks in parallel computing |
| modelDensity | evaluate the density in the current model |
| Mstep | M-step |
| plotGraphs | plot the data matrix, the inferred graph and/or the true binary graph |
| plotICL | plot ICL curve |
| qvaluesNSBM | compute q-values in the noisy stochastic block model |
| q_delta_ql | auxiliary function for the computation of q-values |
| res_exp | Output of fitNSBM() on a dataset applied in the exponential NSBM |
| res_gamma | Output of fitNSBM() on a dataset applied in the Gamma NSBM |
| res_gauss | Output of fitNSBM() on a dataset applied in the Gaussian NSBM |
| rnsbm | simulation of a graph according the noisy stochastic block model |
| spectralClustering | spectral clustering with absolute values |
| tauDown | Create new initial values by merging pairs of groups of provided tau |
| tauUp | Create new values of tau by splitting groups of provided tau |
| tauUpdate | Compute one iteration to solve the fixed point equation in the VE-step |
| update_newton_gamma | Perform one iteration of the Newton-Raphson to compute the MLE of the parameters of the Gamma distribution |
| VEstep | VE-step |