Exact(13)
McSharry, P. E. & Smith, L. A. Consistent nonlinear dynamics: identifying model inadequacy.
The Bayesian constant mean model (high model inadequacy) had marked prediction uncertainty which was reduced by accounting for the effects of environmental covariates in the Bayesian linear trend model (low model inadequacy), indicating that model inadequacy had a negative impact on prediction uncertainty.
Many experiments in the physical and engineering sciences study complex processes in which bias due to model inadequacy dominates random error.
The model contains error terms for model inadequacy (model or process error) and for the sampling error in the estimated spatial means.
The observed model-data discrepancies are primarily due to model inadequacy, such as our simplified modeling of the bulk soil electrical conductivity profile.
The effects of some types of model inadequacy have been demonstrated on an automated system for experimental design to determine optimum conditions in a situation typical of process development.
Similar(47)
Model inadequacies include experimental designs that do not incorporate biological concepts, drug pharmacology, or toxicity.
Measured and analytical data are unlikely to be equal due to measured noise, model inadequacies, structural damage, etc.
Measured and analytical data are unlikely to be equal due to measured noise, model inadequacies and structural damage, etc.
These uncertainties were mapped and appeared to be related to some local model inadequacies and to small-scale variability of soil moisture.
The proposed methodology accounts for uncertainties in the model parameters as well as physical model inadequacies, providing estimates of the rate constant that reflect both types of uncertainties.
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