Showing 1 - 7 of 7
Persistent link: https://www.econbiz.de/10011974096
Taking agent-based models (ABM) closer to the data is an open challenge. This paper explicitly tackles parameter space exploration and calibration of ABMs combining supervised machine-learning and intelligent sampling to build a surrogate meta-model. The proposed approach provides a fast and...
Persistent link: https://www.econbiz.de/10011630888
Persistent link: https://www.econbiz.de/10011708084
We propose a novel approach to the statistical analysis of simulation models and, especially, agent-based models (ABMs). Our main goal is to provide a fully automated and model-independent tool-kit to inspect simulations and perform counter-factual analysis. Our approach: (i) is easy-to-use by...
Persistent link: https://www.econbiz.de/10012308914
Efficiently calibrating agent-based models (ABMs) to real data is an open challenge. This paper explicitly tackles parameter space exploration and calibration of ABMs by combining machine-learning and intelligent iterative sampling. The proposed approach "learns" a fast surrogate meta-model...
Persistent link: https://www.econbiz.de/10012959840
Persistent link: https://www.econbiz.de/10013542997
Although high-resolution gridded climate variables are provided by multiple sources, the need for country and region-specific climate data weighted by indicators of economic activity is becoming increasingly common in environmental and economic research. We process available information from...
Persistent link: https://www.econbiz.de/10014450634