Assessing first-order emulator inference for physical parameters in nonlinear mechanistic models
Journal of Agricultural, Biological, and Environmental Statistics
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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.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Assessing first-order emulator inference for physical parameters in nonlinear mechanistic models |
| Series title | Journal of Agricultural, Biological, and Environmental Statistics |
| DOI | 10.1007/s13253-011-0073-7 |
| Volume | 16 |
| Issue | 4 |
| Year Published | 2011 |
| Language | English |
| Publisher | Springer |
| Publisher location | Amsterdam, Netherlands |
| Contributing office(s) | Colorado Cooperative Fish and Wildlife Research Unit |
| Description | 20 p. |
| Larger Work Type | Article |
| Larger Work Subtype | Journal Article |
| Larger Work Title | Journal of Agricultural, Biological, and Environmental Statistics |
| First page | 475 |
| Last page | 494 |
| Google Analytic Metrics | Metrics page |