A unified interface for relational event history analysis. The package re-exports key functions from 'remify', 'remstats', and 'remstimate' to support a streamlined workflow from data processing to model estimation and diagnosis.
The remverse package provides a unified interface to a set of R packages for the analysis of relational event
history data. It re-exports the main workflow functions and commonly used effects from its core packages, allowing
users to work with a single package entry point. Additional, more specialised functionality remains available in the
individual packages. These packages are (at the moment):
| Core package name | Short description |
|---|---|
remify |
A package that transforms REH data from other packages (hence: in other formats) or other sources to a REH structure that can be used in our packages (and, potentially, vice versa) |
remstats |
Computation of statistics (network-based and not) which are finally arranged within a data structure that is suitable for the other core packages |
remstimate |
Functions for the optimization of the likelihood, for the estimation of parameters in a bayesian fashion and other functions that are useful for handling the data structure of a REH. |
Packages that will be added later:
| Core package name | Short description |
|---|---|
rembrandt |
Functions for visualization and descriptive (quantitative and qualitative) analysis of a REH |
bremory |
A semiparametric method to inquire about the presence of memory in a REH |
remdata |
A package with REH datasets |
remulate |
Package to generate/simulate/emulate REH data |
| ... | ... |
The package contains code written in:
(languages used across all the minor packages)
To install the package in R using devtools (when available as an R package):
library(devtools)
install_github("TilburgNetworkGroup/remverse")
# load the package
library(remverse)
See the NEWS file for the most up to date changes.