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.
- Version1.3.1
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- rem citation info
- Last release10/25/2018
Team
Laurence Brandenberger
Insights
Last 30 days
This package has been downloaded 185 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 1 times.
Last 365 days
This package has been downloaded 2,587 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Jan 24, 2024 with 126 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports3 packages
- Suggests3 packages
- Linking To1 package