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README.md

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@@ -15,6 +15,7 @@ The following model calibration methods have been evaluated.
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* [Differential Evolution Adaptive Metropolis](https://github.com/JBris/model-calibration-evaluation/tree/main/pipelines/dream/run.py)
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* [Experimental Design via Gaussian Process Emulation](https://github.com/JBris/model-calibration-evaluation/tree/main/pipelines/experimental_design/run.py)
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* [Flow Matching Posterior Estimation](https://github.com/JBris/model-calibration-evaluation/tree/main/pipelines/fmpe/run.py)
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* [Genetic Algorithm](https://github.com/JBris/model-calibration-evaluation/tree/main/pipelines/evotorch/run.py)
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* [Tree-structured Parzen Estimator](https://github.com/JBris/model-calibration-evaluation/tree/main/pipelines/optimisation/run.py)
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* [Polynomial Chaos Expansion](https://github.com/JBris/model-calibration-evaluation/tree/main/pipelines/poly_chaos/run.py)
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* [Polynomial Chaos Kriging](https://github.com/JBris/model-calibration-evaluation/tree/main/pipelines/poly_chaos_kriging/run.py)

data/evolutionary/config.yaml

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mu: 52.5
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mu_lb: 45
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mu_ub: 60
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n: 100
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seed: 100
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sigma: 13.5
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sigma_lb: 5
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sigma_ub: 20

data/evolutionary/trace.csv

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pop_best_eval,mean_eval,median_eval,best_eval,worst_eval
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0.14078836143016815,0.8988283276557922,0.9279986023902893,0.14078836143016815,94.46417236328125
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0.038443926721811295,0.5685918927192688,0.6136226058006287,0.038443926721811295,94.46417236328125

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