Package: multiness 1.0.2.9000

multiness: MULTIplex NEtworks with Shared Structure

Model fitting and simulation for Gaussian and logistic inner product MultiNeSS models for multiplex networks. The package implements a convex fitting algorithm with fully adaptive parameter tuning, including options for edge cross-validation. For more details see MacDonald et al., (2022) <https://doi.org/10.1093/biomet/asab058>.

Authors:Peter W. MacDonald [aut, cre]

multiness_1.0.2.9000.tar.gz
multiness_1.0.2.9000.zip(r-4.5)multiness_1.0.2.9000.zip(r-4.4)multiness_1.0.2.9000.zip(r-4.3)
multiness_1.0.2.9000.tgz(r-4.5-any)multiness_1.0.2.9000.tgz(r-4.4-any)multiness_1.0.2.9000.tgz(r-4.3-any)
multiness_1.0.2.9000.tar.gz(r-4.5-noble)multiness_1.0.2.9000.tar.gz(r-4.4-noble)
multiness_1.0.2.9000.tgz(r-4.4-emscripten)multiness_1.0.2.9000.tgz(r-4.3-emscripten)
multiness.pdf |multiness.html✨
multiness/json (API)
NEWS

# Install 'multiness' in R:
install.packages('multiness', repos = c('https://peterwmacd.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/peterwmacd/multiness/issues

Datasets:

On CRAN:

Conda:

3.32 score 42 scripts 168 downloads 5 exports 11 dependencies

Last updated 2 years agofrom:ee062885d7. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 20 2025
R-4.5-winOKMar 20 2025
R-4.5-macOKMar 20 2025
R-4.5-linuxOKMar 20 2025
R-4.4-winOKMar 20 2025
R-4.4-macOKMar 20 2025
R-4.4-linuxOKMar 20 2025
R-4.3-winOKMar 20 2025
R-4.3-macOKMar 20 2025

Exports:aseexpitlogitmultiness_fitmultiness_sim

Dependencies:codetoolsforeachglmnetiteratorslatticeMatrixRcppRcppEigenRSpectrashapesurvival