arXiv · 2109.10208
Bayes Linear Emulation of Simulated Crop Yield
Abstract
The analysis of the output from a large scale computer simulation experiment can pose a challenging problem in terms of size and computation. We consider output in the form of simulated crop yields from the Environmental Policy Integrated Climate (EPIC) model, which requires a large number of inputs such as fertiliser levels, weather conditions, and crop rotations inducing a high dimensional input space. In this paper, we adopt a Bayes linear approach to efficiently emulate crop yield as a function of the simulator fertiliser inputs. We explore emulator diagnostics and present the results from emulation of a subset of the simulated EPIC data output.
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Muhammad Mahmudul Hasan, Jonathan A. Cumming. 2021-09-21. Bayes Linear Emulation of Simulated Crop Yield. https://doi.org/10.1007/978-3-030-86133-9_7
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