R: Handling Missing Data in Stochastic Block Models

# Handling Missing Data in Stochastic Block Models

## Documentation for package ‘missSBM’ version 1.1.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

blockDyadSampler | Class for defining a block dyad sampler
blockDyadSampling_fit | Class for fitting a block-dyad sampling
blockNodeSampler | Class for defining a block node sampler
blockNodeSampling_fit | Class for fitting a block-node sampling
coef.missSBM_fit | Extract model coefficients
covarDyadSampling_fit | Class for fitting a dyad sampling with covariates
covarNodeSampling_fit | Class for fitting a node-centered sampling with covariate
degreeSampler | Class for defining a degree sampler
degreeSampling_fit | Class for fitting a degree sampling
doubleStandardSampler | Class for defining a double-standard sampler
doubleStandardSampling_fit | Class for fitting a double-standard sampling
dyadSampler | Virtual class for all dyad-centered samplers
dyadSampling_fit | Class for fitting a dyad sampling
er_network | ER ego centered network
estimateMissSBM | Estimation of simple SBMs with missing data
fitted.missSBM_fit | Extract model fitted values from object 'missSBM_fit', return by 'estimateMissSBM()'
frenchblog2007 | Political Blogosphere network prior to 2007 French presidential election
l1_similarity | L1-similarity
missSBM_collection | An R6 class to represent a collection of SBM fits with missing data
missSBM_fit | An R6 class to represent an SBM fit with missing data
missSBM_param | Control of a missSBM fit
networkSampler | Definition of R6 Class 'networkSampling_sampler'
networkSampling | Definition of R6 Class 'networkSampling'
networkSamplingDyads_fit | Virtual class used to define a family of networkSamplingDyads_fit
networkSamplingNodes_fit | Virtual class used to define a family of networkSamplingNodes_fit
nodeSampler | Virtual class for all node-centered samplers
nodeSampling_fit | Class for fitting a node sampling
observeNetwork | Observe a network partially according to a given sampling design
partlyObservedNetwork | An R6 Class used for internal representation of a partially observed network
plot.missSBM_fit | Visualization for an object 'missSBM_fit'
predict.missSBM_fit | Prediction of a 'missSBM_fit' (i.e. network with imputed missing dyads)
predicted.missSBM_fit | Prediction of a 'missSBM_fit' (i.e. network with imputed missing dyads)
simpleDyadSampler | Class for defining a simple dyad sampler
simpleNodeSampler | Class for defining a simple node sampler
SimpleSBM_fit | Base internal class for adjusting a binary Stochastic Block Model in the context of missSBM.
SimpleSBM_fit_MNAR | Internal class for a binary SBM fit under MNAR sampling designs (double-standard, block-node, block-dyad).
SimpleSBM_fit_noCov | Internal class for a binary SBM fit under MAR sampling designs without covariates.
SimpleSBM_fit_withCov | Internal class for a binary SBM fit under MAR sampling designs with covariates.
snowballSampler | Class for defining a snowball sampler
summary.missSBM_fit | Summary method for a 'missSBM_fit'
war | War data set