CE-ABC is a code to simulate the epidemic outbreaks with mechanistic models through a cross-entropy approximate Bayesian framework.
CE-ABC: Cross-Entropy Approximate Bayesian Computation is a Matlab package that implements a framework for uncertainty quantification in mechanistic epidemic models defined by ordinary differential equations, which combines the cross-entropy method for optimization and approximate Bayesian computation for statistical inference. With some straightforward adaptations, CE-ABC strategy can also be applied to other systems (mechanical, electrical, coupled, etc). More details are in the following paper:
Preprint available at: https://arxiv.org/abs/2207.12111
Simulations done with CE-ABC are fully reproducible, as can be seen on this CodeOcean capsule.
We ask the code users to cite the following manuscript in any publications reporting work done with our code:
@article{CunhaJr2023p,
author = {A {Cunha~Jr} and D. A. W. Barton and T. G. Ritto},
title = {Uncertainty quantification in mechanistic epidemic models via cross-entropy approximate Bayesian computation},
journal = {Nonlinear Dynamics},
year = {2023},
volume = {111},
pages = {9649–9679},
doi = {10.1007/s11071-023-08327-8},
}
CE-ABC is released under the MIT license. See the LICENSE file for details. All new contributions must be made under the MIT license.