AUC                     Negative AUC for matrix predictions
ECV.for.blockmodel      Edge Cross-Validation for blockmodel selection
ECV.undirected.Rank     Edge Cross-Validation for RDPG rank selection
NCV.for.blockmodel      Node Cross-Validation for blockmodel selection
SBM.prob                Estimate SBM connection probabilities and
                        negative log-likelihood
SBM.spectral.clustering
                        Spectral clustering for a Stochastic Block
                        Model
best.perm.label.match   Find the best permutation label matching
bin.dev                 Binomial deviance loss
blockmodel.gen.fast     Generate a fast SBM or DCBM network (sparse)
community.sim           Simulate a Stochastic Block Model network
community.sim.sbm       Simulate an SBM with distance-decaying block
                        probabilities
croissant.blockmodel    CROISSANT for blockmodel selection
croissant.latent        CROISSANT for latent space model dimension
                        selection
croissant.rdpg          CROISSANT for RDPG rank selection
croissant.tune.regsp    CROISSANT for regularisation parameter tuning
                        in spectral methods
edge.index.map          Map a linear edge index to row-column indices
                        in the upper triangle
eigen.DCBM.est          Eigenvector-based DCBM estimation
fast.DCBM.est           Fast DCBM parameter estimation
fast.SBM.est            Fast SBM block probability estimation
l2                      L2 loss between two matrices
latent.gen              Generate a latent space network
matched.lab             Apply label permutation to match reference
neglog                  Safe negative log-likelihood term
nscv.f.fold             Inductive Node-Splitting Cross-Validation with
                        f-fold splitting
nscv.random.split       Inductive Node-Splitting Cross-Validation with
                        random node splits
sparse.RDPG.gen         Generate a sparse RDPG network
