bremory

The package is currently being upgraded, its full functionalities will be available in the coming weeks - May, 2023

Modeling Memory Retention in Relational Event Data

The bremory package offers several methods for inquiring about the presence of memory in relational event networks:

a bayesian semi-parametric approach for modeling memory decay (Arena et al. 2022)
a parametric approach for modeling memory decay in one-type relational event networks (Arena et al. 2023)
a parametric approach for modeling type-related memory decays (method not yet published)

Installation

Install the package in R using devtools or remotes:

# via `devtools`
devtools::install_github(repo = "TilburgNetworkGroup/bremory", build_vignettes = TRUE)

# via `remotes`
remotes::install_github(repo = "TilburgNetworkGroup/bremory", build_vignettes = TRUE)

Vignettes

List all the vignettes available with the installed version of bremory

vignette(package = "bremory")

Author

Giuseppe Arena, Tilburg University (Tilburg, The Netherlands). (g.arena@tilburguniversity.edu)

Funding

The funder of this work is the ERC and the ERC project number is 758791.

References

Arena, G., Mulder, J., & Leenders, R. Th. A. J. (2022). A Bayesian Semi-Parametric Approach for Modeling Memory Decay in Dynamic Social Networks. Sociological Methods & Research, 0(0). https://doi.org/10.1177/00491241221113875

Arena, G., Mulder, J., & Leenders, R. (2023). How fast do we forget our past social interactions? Understanding memory retention with parametric decays in relational event models. Network Science, 1-28. doi:10.1017/nws.2023.5