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: * R (>= 4.0.0) * Rcpp (>= 1.0.4.6) and RcppArmadillo (>= 0.9.860.2.0) * C++11 (Compiler Version: GCC-8.1.0)
(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.