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Our model requires parameter values appropriate for specific patients.
The AIM-2 model requires parameter values for the leakage coefficient and pressure exponent for individual homes that are derived from whole-building pressurization tests.
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The hydrological model requires parameters predominantly related to soil physics, for example, P0 (Eq. (13)), Ks, Ds, a, b, θmin, θmax (Eq. (16)) and p (Eq. (23)).
The optimum design of experiments for nonlinear models requires parameter sensitivities, that is the derivatives of the response with respect to the parameters.
While FISH measurements have been used to establish a connection between the mean square distance of two markers and genomic separation [8], [12], [40], a direct comparison to polymer models requires parameters to map one model bead to physical units like nanometers and base pairs.
The fundamental challenge is that such models require parameters that are driven by data, but there are very few good examples of research on mixtures at environmentally relevant dose levels (502) (c.f. Porter et al. (510)), and there are fewer still that are focused on cancer.
However, making quantitative predictions with such models often requires parameter estimation from data, raising questions of parameter identifiability and estimability.
The model requires few parameters from the load displacement curve obtained in a pull-out experiment.
Our model requires three parameters: α, β, and Da.
The cubic spline model requires 70+ clusters parameters to be sampled per cycle.
This could be due to the fact that the covarion model requires less parameters than the 2-components MBL model.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com