Assessing First-Order Emulator Inference for Physical Parameters in Nonlinear Mechanistic Models |
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Authors: | Mevin B Hooten William B Leeds Jerome Fiechter Christopher K Wikle |
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Institution: | (1) Physics-Physical Oceanography, Memorial University Newfoundland, St. John’s, NL, A1C 5S7, Canada;; |
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Abstract: | We present an approach for estimating physical parameters in nonlinear models that relies on an approximation to the mechanistic
model itself for computational efficiency. The proposed methodology is validated and applied in two different modeling scenarios:
(a) Simulation and (b) lower trophic level ocean ecosystem model. The approach we develop relies on the ability to predict
right singular vectors (resulting from a decomposition of computer model experimental output) based on the computer model
input and an experimental set of parameters. Critically, we model the right singular vectors in terms of the model parameters
via a nonlinear statistical model. Specifically, we focus our attention on first-order models of these right singular vectors
rather than the second-order (covariance) structure. |
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Keywords: | |
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