lame: Longitudinal Additive and Multiplicative Effects Models for Networks

Additive and multiplicative effects models for both cross-sectional and longitudinal network analysis. The package provides two main functions: ame() for cross-sectional networks and lame() for longitudinal networks. It supports square and rectangular network structures. Key features include: (1) Cross-sectional network analysis via ame() with support for binary, continuous, ordinal, and count data; (2) Longitudinal network analysis via lame() with additive sender/receiver and multiplicative latent-factor effects that can evolve over time through AR(1) processes (Sewell and Chen (2015) <doi:10.1080/01621459.2014.988214>; Durante and Dunson (2014) <doi:10.1093/biomet/asu040>); (3) Handling of changing actor compositions across time periods in longitudinal models; (4) Performance improvements through C++ implementations via 'Rcpp' and 'RcppArmadillo'.

Version:	1.3.4
Depends:	R (≥ 3.5.0)
Imports:	Rcpp, ggplot2, ggrepel, ggforce, gridExtra, coda, patchwork, cli, MASS, Matrix, abind, netify (≥ 1.5.3), graphics, grDevices, parallel, stats, utils
LinkingTo:	Rcpp, RcppArmadillo
Suggests:	knitr, rmarkdown, testthat (≥ 3.0.0), igraph, network, posterior, loo, digest, tibble, broom, generics, pROC, precrec, statmod, dplyr, modelsummary, callr, amen
Published:	2026-08-04
DOI:	10.32614/CRAN.package.lame (may not be active yet)
Author:	Cassy Dorff [aut], Shahryar Minhas [aut, cre], Tosin Salau [aut]
Maintainer:	Shahryar Minhas <minhassh at msu.edu>
BugReports:	https://github.com/netify-dev/lame/issues
License:	MIT + file LICENSE
URL:	https://netify-dev.github.io/lame/, https://github.com/netify-dev/lame
NeedsCompilation:	yes
Citation:	lame citation info
Materials:	NEWS
CRAN checks:	lame results

Documentation:

Reference manual:	lame.html , lame.pdf
Vignettes:	Bipartite Network Analysis (source, R code) Your First AME Model (source, R code) Dynamic Effects in Longitudinal AME Models (source, R code) Fast (MCMC-free) AME Estimation (source, R code) Forecasting Longitudinal Networks with lame (source, R code) lame Overview (source, R code) Getting Started with lame (source, R code)

Downloads:

Package source:	lame_1.3.4.tar.gz
Windows binaries:	r-devel: not available, r-release: lame_1.3.4.zip, r-oldrel: lame_1.3.4.zip
macOS binaries:	r-release (arm64): lame_1.3.4.tgz, r-oldrel (arm64): lame_1.3.4.tgz, r-release (x86_64): lame_1.3.4.tgz, r-oldrel (x86_64): lame_1.3.4.tgz

Linking:

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