Package: mlsbm 0.99.4

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).

Authors:Carter Allen [aut, cre], Dongjun Chung [aut]

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mlsbm.pdf |mlsbm.html✨
mlsbm/json (API)

# Install 'mlsbm' in R:

install.packages('mlsbm', repos = c('https://carter-allen.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/carter-allen/mlsbm/issues

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

AL - Simulated 3-layer network data

On CRAN:

10 exports 0.63 score 68 dependencies 1 scripts 180 downloads

Last updated 3 years agofrom:f42504b709. Checks:OK: 9. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Sep 06 2024
R-4.5-win-x86_64	OK	Sep 06 2024
R-4.5-linux-x86_64	OK	Sep 06 2024
R-4.4-win-x86_64	OK	Sep 06 2024
R-4.4-mac-x86_64	OK	Sep 06 2024
R-4.4-mac-aarch64	OK	Sep 06 2024
R-4.3-win-x86_64	OK	Sep 06 2024
R-4.3-mac-x86_64	OK	Sep 06 2024
R-4.3-mac-aarch64	OK	Sep 06 2024

Exports:col_summarize fit_mlsbm fit_sbm get_scores mean_CRI plot_connectivity_matrix plot_connectivity_network remap_canonical2 sample_mlsbm sample_sbm

Dependencies:BH BiocGenerics BiocNeighbors BiocParallel bluster cachem cli cluster codetools colorspace cpp11 dplyr fansi farver fastmap formatR futile.logger futile.options generics ggforce ggplot2 ggraph ggrepel glue graphlayouts gridExtra gtable igraph isoband labeling lambda.r lattice lifecycle magrittr MASS Matrix memoise mgcv munsell nlme patchwork pillar pkgconfig polyclip purrr R6 RColorBrewer Rcpp RcppArmadillo RcppEigen RcppHNSW rlang S4Vectors scales snow stringi stringr systemfonts tibble tidygraph tidyr tidyselect tweenr utf8 vctrs viridis viridisLite withr

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Simulated 3-layer network data	AL
The col_summarize function	col_summarize
R/Rcpp function for fitting multilevel stochastic block model	fit_mlsbm
R/Rcpp function for fitting single level stochastic block model	fit_sbm
Calculate continuous uncertainty scores	get_scores
The mean_CRI function	mean_CRI
mypackage: A package for fitting single and multilevel SBMs.	mlsbm
Plot community structure of cell sub-populations as matrix	plot_connectivity_matrix
Plot community structure parameters as a K x K network	plot_connectivity_network
Canonical re-mapping of mixture component labels	remap_canonical2
R/Rcpp function for sampling from a multilevel stochastic block model	sample_mlsbm
R/Rcpp function for sampling from a single level stochastic block model	sample_sbm