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Model calibration as a testing strategy for system dynamics models
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“If the full model is then estimated by matching the historical trajectories, the calibration processes varies the model parameters to match the observed patterns, even if those patterns have resulted from external noise that we cannot replicate within the model. As a result, the model parameters would be mis-specified even if the overall behavior appears to fit the empirical trends (40).”
From Modeling the hypothalamus-pituitary-adrenal axis: A review and extension (2015) · cites this paper as [40]
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Metadata
- Authors
- Oliva, R.
- Affiliations
- Harvard University (US)
- Corresponding author
- Oliva, Rogelio
- ORCID
- Oliva, Rogelio
- Venue
- European Journal of Operational Research
- Publisher
- Elsevier BV
- Published
- 2003-12
- Volume
- 151
- Issue
- 3
- Pages
- 552-568
- ISSN
- 0377-2217 (ISSN-L)
- OpenAlex
- W2150086489
- Cited by
- 314
- References
- 68
- Citations by year
- 2026: 17 · 2025: 18 · 2024: 20 · 2023: 12 · 2022: 14 · 2021: 14 · 2020: 23 · 2019: 16 · 2018: 21 · 2017: 19 · 2016: 27 · 2015: 19 · 2014: 14 · 2013: 13 · 2012: 12
- FWCI
- 7.55
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- European Journal of Operational Research (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Complex Systems and Decision Making
- Social Sciences › Decision Sciences › Management Science and Operations Research › Simulation Techniques and Applications
- Physical Sciences › Mathematics › Modeling and Simulation › Modeling and Simulation Systems
- Keywords
- system dynamics modeling, model calibration, model testing, hypothesis testing, structure-behavior relationship, parameter estimation, model validation, decision-making
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