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', presented in 'Barbillon, Chiquet and Tabouy' (2022) <doi:10.18637/jss.v101.i12>, 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>.
Package details |
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Maintainer | Julien Chiquet <julien.chiquet@inrae.fr> |
License | GPL-3 |
Version | 1.0.4 |
URL | https://grosssbm.github.io/missSBM/ |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
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