Learn R Programming

rem (version 1.3.1)

Relational Event Models (REM)

Description

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.

Copy Link

Version

Install

install.packages('rem')

Monthly Downloads

229

Version

1.3.1

License

GPL (>= 2)

Maintainer

Laurence Brandenberger

Last Published

October 25th, 2018

Functions in rem (1.3.1)

reciprocityStat

Calculate reciprocity statistics
inertiaStat

Calculate inertia statistics
timeToEvent

Calculate the time-to-next-event or the time-since-date for a REM data set.
triadStat

Calculate triad statistics
rem-package

Fit Relational Event Models (REM)
similarityStat

Calculate similarity statistics
createRemDataset

Create REM data set with dynamic risk sets
degreeStat

Calculate (in/out)-degree statistics
eventSequence

Create event sequence
fourCycleStat

Calculate four cycle statistics