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]

mlsbm_0.99.4.tar.gz
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mlsbm_0.99.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
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:

cpp

2.70 score 2 scripts 250 downloads 10 exports 74 dependencies

Last updated from:f42504b709. Checks:15 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	192
linux-devel-x86_64	OK	231
source / vignettes	OK	248
linux-release-arm64	OK	211
linux-release-x86_64	OK	253
macos-release-arm64	OK	166
macos-release-x86_64	OK	423
macos-oldrel-arm64	OK	316
macos-oldrel-x86_64	OK	372
windows-devel-arm64	OK	416
windows-devel-x86_64	OK	247
windows-release-arm64	OK	442
windows-release-x86_64	OK	203
windows-oldrel-x86_64	OK	182
wasm-release	OK	144

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

Dependencies:abind assorthead base64enc beachmat BH BiocGenerics BiocNeighbors BiocParallel bluster cachem cli cluster codetools cpp11 DelayedArray dplyr farver fastmap formatR futile.logger futile.options generics ggforce ggplot2 ggraph ggrepel glue graphlayouts gridExtra gtable igraph IRanges isoband jsonlite labeling lambda.r lattice lifecycle magrittr MASS Matrix MatrixGenerics matrixStats memoise patchwork pillar pkgconfig polyclip purrr R6 RColorBrewer Rcpp RcppArmadillo rlang S4Arrays S4Vectors S7 scales snow SparseArray stringi stringr systemfonts tibble tidygraph tidyr tidyselect tweenr utf8 vctrs viridis viridisLite withr XVector

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