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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "epiworldRcalibrate" in publications use:'
type: software
license: MIT
title: 'epiworldRcalibrate: Fast and Effortless Calibration of Agent-Based Models
  using Machine Learning'
version: 0.1.3
identifiers:
- type: doi
  value: 10.32614/CRAN.package.epiworldRcalibrate
abstract: Provides tools and pre-trained Machine Learning [ML] models for calibration
  of Agent-Based Models [ABMs] built with the R package 'epiworldR'. Implements methods
  described in Najafzadehkhoei, Vega Yon, Modenesi, and Meyer (2025) <https://doi.org/10.48550/arXiv.2509.07013>.
  Users can automatically calibrate ABMs in seconds with pre-trained ML models, effectively
  focusing on simulation rather than calibration. Bridges a gap by allowing public
  health practitioners to run their own ABMs without the advanced technical expertise
  often required by calibration.
authors:
- family-names: Najafzadehkhoei
  given-names: Sima
  email: sima.njf@utah.edu
  orcid: https://orcid.org/0009-0002-6253-2910
- family-names: Vega Yon
  given-names: George
  email: g.vegayon@gmail.com
  orcid: https://orcid.org/0000-0002-3171-0844
- family-names: Wagoner
  given-names: Jake
  email: jakew@sci.utah.edu
- family-names: Modenesi
  given-names: Bernardo
  email: bmodenesi@gmail.com
preferred-citation:
  type: manual
  title: 'epiworldRcalibrate: Fast and Effortless Calibration of Agent-Based Models
    using Machine Learning'
  authors:
  - family-names: Najafzadehkhoei
    given-names: Sima
    email: sima.njf@utah.edu
    orcid: https://orcid.org/0009-0002-6253-2910
  - family-names: Vega Yon
    given-names: George
    email: g.vegayon@gmail.com
    orcid: https://orcid.org/0000-0002-3171-0844
  - family-names: Modenesi
    given-names: Bernardo
    email: bmodenesi@gmail.com
  year: '2026'
  notes: R package version 0.1.0
  url: https://github.com/sima-njf/epiworldRcalibrate
repository: https://sima-njf.r-universe.dev
repository-code: https://github.com/sima-njf/epiworldRcalibrate
commit: f8a39ce2cbda363fec0d8c10067c3baf45db3938
url: https://sima-njf.github.io/epiworldRcalibrate/
date-released: '2026-04-02'
contact:
- family-names: Najafzadehkhoei
  given-names: Sima
  email: sima.njf@utah.edu
  orcid: https://orcid.org/0009-0002-6253-2910
references:
- type: article
  title: 'Machine Generalize Learning in Agent-Based Models: Going Beyond Surrogate
    Models for Calibration in ABMs'
  authors:
  - family-names: Najafzadehkhoei
    given-names: Sima
  - family-names: Vega Yon
    given-names: George
  - family-names: Modenesi
    given-names: Bernardo
  - family-names: Meyer
    given-names: Derek
  year: '2025'
  journal: arXiv
  notes: '2509.07013'
  url: https://arxiv.org/abs/2509.07013