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Sensitivity analysis shows the model is sensitive to 2 model parameters both of which are concerned with the historic (pre-systematic) period of the time series.
In sum, the Bayesian hierarchical model produces posterior distributions for model parameters both on the individual level and on the group level.
Here we focus on the response of steady-state metabolite concentrations only, and include as model parameters both kinetic constants and enzyme concentrations.
A Bayesian approach was utilized for estimation of the model parameters, both to leverage prior knowledge in estimation of parameters based on the current clinical trial dataset and to compensate for data that was not collected in the study.
We carried out computer simulation and estimation of the model parameters both under a nonlinear weighted least-squares model (naive pooled data approach) and under a nonlinear mixed-effects model.
For each set of these model parameters, both the observed, and synthetic, spectra were normalized in order to put them on a comparable amplitude level.
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The restricted additivity model (Gennings et al. 2004) included only the single-chemical dose response model parameters but used both the single-chemical and mixture data.
The restricted additivity model (Casey et al. 2004) included only the single-chemical dose response model parameters but used both the single-chemical and mixture data.
Simultaneous estimation of PK model parameters for both routes of administration permitted estimation of the bioavailability of the orally administered drug (F 41.
All the model parameters for both the models can be derived from uniaxial tensile tests performed at different strain rates.
The experimental results clearly demonstrate the power of the proposed BBO-M in estimating model parameters of both solar and fuel cells.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com