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The model fitting parameters provide sufficient flexibility to accurately reproduce the dynamics of different units in industrial plants.
d Plot of the error in normalized rate prediction (q D-Data − q D-Model) versus time Table 1 Summary of model fitting parameters obtained for the parallel flow model applied to a well in the dataset q oiT (STB/D) f 1 f 2 f 3 f 4 f T q i1 (STB/D) q i2 (STB/D) q i3 (STB/D) q i4 (STB/D) τ 1 (days) τ 2 (days) τ 3 (days) τ 4 (days) 557 0.3 0 0 0.7 15151 0 0 407 1020 – – 59.
A, K and bg are the model fitting parameters, c is the target jth concentration in pM.
In absence of precise estimates, we use the HSV-2 transmission probability per coital act as one of the model fitting parameters, but constrain its value to be in the range suggested by the empirical data.
In the microarray context, it is generally formulated as a hyperbolic function:
The Langmuir isotherm is a hyperbolic response function (Eq. 1) where Ij is the signal intensity from the probes at target concentration j. a, b and d are the model fitting parameters, and c is the target jth concentration in pM.
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Then, in a second step, a statistical Montecarlo method is used in order to propagate the model fitting parameter uncertainty through the model.
Model fitting parameter estimation was performed in a hierarchical model with empirical priors treating parameters as a random effect.
Statistical comparisons among each model fitted parameter were performed using the t-test (Systat 11, Richmond, VA), for which a p value of <0.05 was considered significant.
The resulting model fit parameters were compared to correctly time-matched and calibrated data fitting results.
Two model fit parameters were used to compare the three models with each other.
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