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Bayesian calibration of stochastic agent based model via random forest

RESOURCE

Publicly Accessible Repository
https://github.com/sandialabs/Bayesian-calibration-of-stochastic-agent-based-model-via-random-forest
https://doi.org/10.11578/dc.20240925.4

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Abstract

SAND2024-11403O The Bayesian Calibration of Stochastic Agent-based Model via Random Forest is a code that was developed in concurrence with an article by the same name that was written for a journal. The code reproduces simulation results and plots from the article. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
Developers:
Robertson, Connor [1][2][3]
  1. Sandia National Lab. (SNL-CA), Livermore, CA (United States)
  2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  3. Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
Release Date:
2024-06-17
Project Type:
Open Source, Publicly Available Repository
Software Type:
Scientific
Programming Languages:
Python
R
Version:
0.1
Licenses:
MIT License
Sponsoring Org.:
Code ID:
144475
Site Accession Number:
SCR #3053.0
Research Org.:
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Country of Origin:
United States

RESOURCE

Publicly Accessible Repository
https://github.com/sandialabs/Bayesian-calibration-of-stochastic-agent-based-model-via-random-forest
https://doi.org/10.11578/dc.20240925.4

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Citation Formats

Robertson, Connor. Bayesian calibration of stochastic agent based model via random forest. Computer Software. https://github.com/sandialabs/Bayesian-calibration-of-stochastic-agent-based-model-via-random-forest. USDOE. 17 Jun. 2024. Web. doi:10.11578/dc.20240925.4.
Robertson, Connor. (2024, June 17). Bayesian calibration of stochastic agent based model via random forest. [Computer software]. https://github.com/sandialabs/Bayesian-calibration-of-stochastic-agent-based-model-via-random-forest. https://doi.org/10.11578/dc.20240925.4.
Robertson, Connor. "Bayesian calibration of stochastic agent based model via random forest." Computer software. June 17, 2024. https://github.com/sandialabs/Bayesian-calibration-of-stochastic-agent-based-model-via-random-forest. https://doi.org/10.11578/dc.20240925.4.
@misc{ doecode_144475,
title = {Bayesian calibration of stochastic agent based model via random forest},
author = {Robertson, Connor},
abstractNote = {SAND2024-11403O The Bayesian Calibration of Stochastic Agent-based Model via Random Forest is a code that was developed in concurrence with an article by the same name that was written for a journal. The code reproduces simulation results and plots from the article. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.},
doi = {10.11578/dc.20240925.4},
url = {https://doi.org/10.11578/dc.20240925.4},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20240925.4}},
year = {2024},
month = {jun}
}