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It is also demonstrated that changing the level of data aggregation can significantly alter the models' parameter values.
Summarizing it can be said that the Bayesian design enables a more detailed interpretation of the model with the same amount of data measured by more efficiently restricting the models parameter values.
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Model parameter values were estimated from the literature.
The model parameter values and model sensitivity tests are also discussed in these studies.
SUV was used for semi-quantitative analysis and model fitting to estimate the model parameter values.
This leads to a fundamental difficulty in estimating model parameter values.
Model parameter values for hypocellular plaque are also given in Table 4 (Loree et al., 1994).
A criterion for maximum error was set to 5%% to derive the model parameter values.
An innovative calibration protocol was applied to evaluate the model parameter values as well.
Output uncertainty bounds were determined as a function of uncertainty in the model parameter values.
It can also improve accuracy for the case of smoothly-variable model parameter values near interfaces.
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