The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
mlsbm: Efficient Estimation of Bayesian SBMs & MLSBMs
Fit Bayesian stochastic block models (SBMs) and multi-level stochastic block models (MLSBMs) using efficient Gibbs sampling implemented in 'Rcpp'. The models assume symmetric, non-reflexive graphs (no self-loops) with unweighted, binary edges. Data are input as a symmetric binary adjacency matrix (SBMs), or list of such matrices (MLSBMs).
| Version: |
0.99.2 |
| Depends: |
R (≥ 2.10) |
| Imports: |
Rcpp |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Published: |
2021-02-07 |
| Author: |
Carter Allen 
[aut, cre],
Dongjun Chung [aut] |
| Maintainer: |
Carter Allen <carter.allen12 at gmail.com> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
yes |
| Materials: |
README |
| CRAN checks: |
mlsbm results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=mlsbm
to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.