epiworldRcalibrate
2026
epidemiology
agent-based models
machine learning
Provides tools and pre-trained Machine Learning (ML) models for calibration of Agent-Based Models (ABMs) built with the R package ‘epiworldR’, implementing methods described in Najafzadehkhoei, Vega Yon, Modenesi, and Meyer (2025).
ActivePackage2026CRAN0.1.4downloads1.3kstars1
Fast and Effortless Calibration of Agent-Based Models using Machine Learning
About
Provides tools and pre-trained Machine Learning (ML) models for calibration of Agent-Based Models (ABMs) built with the R package ‘epiworldR’, implementing methods described in Najafzadehkhoei, Vega Yon, Modenesi, and Meyer (2025). Users can automatically calibrate ABMs in seconds with pre-trained ML models, effectively focusing on simulation rather than calibration, bridging a gap that allows public health practitioners to run their own ABMs without the advanced technical expertise often required by calibration.
Cite
@Manual{epiworldRcalibrate,
title = {epiworldRcalibrate: Fast and Effortless Calibration of Agent-Based Models using Machine Learning},
author = {{Najafzadehkhoei}, {Sima} and {Vega Yon}, {George G.} and {Modenesi}, {Bernardo}},
year = {2026},
doi = {10.32614/CRAN.package.epiworldRcalibrate},
url = {https://cran.r-project.org/package=epiworldRcalibrate},
note = {R package version 0.1.4},
}