R: Random Network Model Estimation, Selection and Parameter Tuning

# Random Network Model Estimation, Selection and Parameter Tuning

## Documentation for package ‘randnet’ version 1.0

- DESCRIPTION file

## Help Pages

randnet-package | Statistical modeling of random networks with model estimation, selection and parameter tuning
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.block | selecting block models by ECV
ECV.nSmooth.lowrank | selecting tuning parameter for neighborhood smoothing estimation of graphon model
ECV.Rank | estimates optimal low rank model for a network
InformativeCore | identify the informative core component of a network
k.core | identify the K-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
network.mixing | estimates network connection probability by network mixing
network.mixing.Bfold | estimates network connection probability by network mixing with B-fold averaging
NMI | calculates normalized mutual information
NSBM.estimate | estimates nomination SBM parameters given community labels by the method of moments
NSBM.Gen | Generates networks from nomination stochastic block model
nSmooth | estimates probabilty matrix by neighborhood smoothing
randnet | Statistical modeling of random networks with model estimation, selection and parameter tuning
RDPG.Gen | generates random networks from random dot product graph model
reg.SP | clusters nodes by regularized spectral clustering
reg.SSP | detects communities by regularized spherical spectral clustering
RightSC | clusters nodes in a directed network by regularized spectral clustering on right singular vectors
SBM.estimate | estimates SBM parameters given community labels
smooth.oracle | oracle smooth graphon estimation
USVT | estimates the network probability matrix by the improved universal singular value thresholding