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
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 | |
| No Results! | ||
Vignettes of missSBM
| Name | ||
| case_study_war_networks.Rmd | ||
| missSBMreferences.bib | ||
| No Results! | ||
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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 |
| imports | ape , corrplot , igraph , magrittr , methods , nloptr , R6 , Rcpp |
| suggests | aricode , blockmodels , covr , ggplot2 , knitr , rmarkdown , testthat |
| depends | R (>= 3.4.0) |
| linkingto | RcppArmadillo |
| Contributors | Pierre Barbillon, Timoth<c3><a9>e Tabouy |
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