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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.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.