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Solving data assimilation problems under uncertainty in basic model parameters and in source terms may require a careful design of the control set.
As such, it is a function of the basic model parameters for these forces.
For Bayesian analyses, the same basic model parameters determined by Modeltest (two substitution rates and gamma distribution) were used.
These basic model parameters indicated that toxicant stress was compensated to a large extent for up to 24 36 h after initiation of MPP+ exposure.
Additional research is required to understand the sensitivity of these different probabilistic measures to the estimated underlying basic model parameters for the treatment effect, and provide some guidance.
With this approach we could use the entire set of N = 155 experimental data points (triplicates) to obtain reliable estimates of the basic model parameters by globally fitting them to the dataset.
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We consider a number of cases, in which basic modeling parameters such as terrain roughness, formation size and shape as well as availability of distance and angle measurements are varied.
A basic model included parameters for fever and respiratory ICD-9 code only.
The large stack was used to verify the ohmic region and to obtain basic stack model parameters.
In this basic model, the parameter σ has a dual role.
There is no difference between the univariate and basic adjusted model parameter estimates for the relationships between same-day temperatures and BPs (Tables 1 and 2).
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