rem: Relational Event Models (REM)

Calculate endogenous network effects in event sequences and fit relational event models (REM): Using network event sequences (where each tie between a sender and a target in a network is time-stamped), REMs can measure how networks form and evolve over time. Endogenous patterns such as popularity effects, inertia, similarities, cycles or triads can be calculated and analyzed over time.

Version: 1.3.1
Depends: R (≥ 2.14.0)
Imports: Rcpp, foreach, doParallel
LinkingTo: Rcpp
Suggests: texreg, statnet, ggplot2
Published: 2018-10-25
DOI: 10.32614/CRAN.package.rem
Author: Laurence Brandenberger
Maintainer: Laurence Brandenberger <lbrandenberger at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: rem citation info
CRAN checks: rem results


Reference manual: rem.pdf


Package source: rem_1.3.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): rem_1.3.1.tgz, r-oldrel (arm64): rem_1.3.1.tgz, r-release (x86_64): rem_1.3.1.tgz, r-oldrel (x86_64): rem_1.3.1.tgz
Old sources: rem archive


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