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Assessing First-Order Emulator Inference for Physical Parameters in Nonlinear Mechanistic Models

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Assessing First-Order Emulator Inference for Physical Parameters in Nonlinear Mechanistic Models; 2011; Article; Journal; Journal of Agricultural, Biological, and Environmental Statistics; Hooten, M. B.; Leeds, W. B.; Fiechter, J.; Wikle, C. K.

Summary

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 [...]

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Type Scheme Key
local-index unknown 70032483
local-pk unknown 70032483
doi http://www.loc.gov/standards/mods/mods-outline-3-5.html#identifier doi:10.1007/s13253-011-0073-7
series unknown Journal of Agricultural, Biological, and Environmental Statistics

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citationTypeArticle
journalJournal of Agricultural, Biological, and Environmental Statistics
languageEnglish
parts
typevolume
value16
typeissue
value4

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