missSBM v0.2.0

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Handling Missing Data in Stochastic Block Models

When a network is partially observed (here, NAs in the adjacency matrix rather than 1 or 0 due to missing information between node pairs), it is possible to account for the underlying process that generates those NAs. 'missSBM' adjusts the popular stochastic block model from network data sampled under various missing data conditions, as described in Tabouy, Barbillon and Chiquet (2019) <doi:10.1080/01621459.2018.1562934>.

Readme

missSBM: Handling missing data in Stochastic Block Models

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When a network is partially observed (here, missing dyads, that is, entries with NA in the adjacency matrix rather than 1 or 0), it is possible to account for the underlying process that generates those NAs. missSBM is an R package for adjusting the popular Stochastic Block Models from network data sampled under various missing data conditions.

Installation

devtools::install_github("jchiquet/missSBM")

Reference

Please cite our work using the following reference:

Timothée Tabouy, Pierre Barbillon & Julien Chiquet (2019) “Variational Inference for Stochastic Block Models from Sampled Data”, Journal of the American Statistical Association, DOI: 10.1080/01621459.2018.1562934

Functions in missSBM

Name Description
missSBM_collection An object to represent a collection of missSBM_fit
estimate Estimation of SBMs with missing data
sample Sampling of network data
war War data set
smooth Smooth the path ICL in a collection of missSBM_fit models
frenchblog2007 Political Blogosphere network prior to 2007 French presidential election
dyadSampler Virtual class for all dyad-centered samplers
simulate Simulation of an SBM
er_network ER ego centred network
SBM_fit R6 Class definition of an SBM-fit
networkSampler Definition of R6 Class 'networkSampling_sampler'
missSBM_fit R6 Class definition of an SBM-fit
networkSampling Definition of R6 Class 'networkSampling'
networkSamplingDyads_fit Virtual class used to define a family of networkSamplingDyads_fit
SBM_sampler An R6 Class to represent a sampler for a SBM
networkSamplingNodes_fit Virtual class used to define a family of networkSamplingNodes_fit
%>% Pipe operator
missSBM Adjusting Stochastic Block Models under various missing data conditions
sampledNetwork An R6 Class to represent sampled network data
prepare_data Prepare network data for estimation with missing data
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Vignettes of missSBM

Name
case_study_war_networks.Rmd
missSBMreferences.bib
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Details

Type Package
URL https://jchiquet.github.io/missSBM
BugReports https://github.com/jchiquet/missSBM/issues
License GPL-3
Encoding UTF-8
LazyData true
RoxygenNote 6.1.1
LinkingTo Rcpp, RcppArmadillo
Collate 'RcppExports.R' 'SBM-Class.R' 'SBM_fit-Class.R' 'SBM_fit_covariates-Class.R' 'SBM_fit_nocovariate-Class.R' 'SBM_sampler-Class.R' 'er_network.R' 'estimate.R' 'frenchblog2007.R' 'missSBM-package.R' 'utils_missSBM.R' 'networkSampling-Class.R' 'networkSampling_fit-Class.R' 'missSBM_fit-Class.R' 'missSBM_collection-Class.R' 'networkSampler-Class.R' 'prepare_data.R' 'sample.R' 'sampledNetwork-Class.R' 'simulate.R' 'utils-pipe.R' 'utils_initialization.R' 'war.R'
VignetteBuilder knitr
NeedsCompilation yes
Packaged 2019-06-07 12:08:02 UTC; jchiquet
Repository CRAN
Date/Publication 2019-06-08 08:10:03 UTC

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