ARI                     Evalute the adjusted Rand index
ICL_Q                   computation of the Integrated Classification
                        Likelihood criterion
J.gamma                 evaluate the objective in the Gamma model
JEvalMstep              evaluation of the objective in the Gauss model
Mstep                   M-step
VEstep                  VE-step
addRowToTau             split group q of provided tau randomly into two
                        into
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
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
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
plotGraphs              plot the data matrix, the inferred graph and/or
                        the true binary graph
plotICL                 plot ICL curve
q_delta_ql              auxiliary function for the computation of
                        q-values
qvaluesNSBM             compute q-values in the noisy stochastic block
                        model
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
