EnsembleKalmanProcesses.jl: Derivative-freeensemble-based model calibration
Oliver R. A. Dunbar, Ignacio Lopez‐Gomez, Alfredo Garbuno-Iñigo, Daniel Zhengyu Huang, Eviatar Bach, Jinlong Wu
Abstract
EnsembleKalmanProcesses.jl is a Julia-based toolbox that can be used for a broad class of black-box gradient-free optimization problems. Specifically, the tools enable the optimization, or calibration, of parameters within a computer model in order to best match user-defined outputs of the model with available observed data Some of the tools can also approximately quantify parametric uncertainty (Huang, Huang, et al., 2022). Though the package is written in Julia Furthermore, the calibration tools are non-intrusive, relying only on the ability of users to compute an output of their model given a parameter value.
Topics & Concepts
CalibrationDerivative (finance)Computer scienceMathematicsStatisticsEconomicsFinancial economicsModel Reduction and Neural NetworksMeteorological Phenomena and SimulationsSeismic Imaging and Inversion Techniques