BHMC.estimate           Estimates the number of communities under block
                        models by the spectral methods
BlockModel.Gen          Generates networks from degree corrected
                        stochastic block model
ConsensusClust          clusters nodes by concensus (majority voting)
                        initialized by regularized spectral clustering
DCSBM.estimate          Estimates DCSBM model
ECV.Rank                estimates optimal low rank model for a network
ECV.block               selecting block models by ECV
ECV.nSmooth.lowrank     selecting tuning parameter for neighborhood
                        smoothing estimation of graphon model
InformativeCore         identify the informative core component of a
                        network
LRBIC                   selecting number of communities by asymptotic
                        likelihood ratio
LSM.PGD                 estimates inner product latent space model by
                        projected gradient descent
NCV.select              selecting block models by NCV
NMI                     calculates normalized mutual information
NSBM.Gen                Generates networks from nomination stochastic
                        block model
NSBM.estimate           estimates nomination SBM parameters given
                        community labels by the method of moments
RDPG.Gen                generates random networks from random dot
                        product graph model
RightSC                 clusters nodes in a directed network by
                        regularized spectral clustering on right
                        singular vectors
SBM.estimate            estimates SBM parameters given community labels
USVT                    estimates the network probability matrix by the
                        improved universal singular value thresholding
k.core                  identify the K-core component of a network
nSmooth                 estimates probabilty matrix by neighborhood
                        smoothing
network.mixing          estimates network connection probability by
                        network mixing
network.mixing.Bfold    estimates network connection probability by
                        network mixing with B-fold averaging
randnet-package         Statistical modeling of random networks with
                        model estimation, selection and parameter
                        tuning
reg.SP                  clusters nodes by regularized spectral
                        clustering
reg.SSP                 detects communities by regularized spherical
                        spectral clustering
smooth.oracle           oracle smooth graphon estimation
