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For the remaining 11 parameters, the data for healthy participants were considered as reference values.
By changing the lattice parameters the data hold time can be changed in a desired way.
For the different measured parameters, the data are presented in terms of percentage, either increased or decreased.
Eventually, to access the kinetic parameters, the data with different concentrations results were analyzed using pseudo-first-order, pseudo-second-order and intraparticle diffusion models.
In order to produce comparable parameters, the data have been reexamined using simple models (homogeneous domain, steady-state flow regime, single porosity).
With these models and parameters, the data term E W D is designed to give penalty to the mis-labeled pixels (e.g., labeled 1 while it is close to ghost).
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Due to the large Pareto shape parameter, the data are roughly Gaussian, resulting in the WMF performing very well.
We conclude by examining the parameters of the data collection process that affect the computation.
In statistical inference, the goal is to obtain estimates of the unknown parameters given the data.
The variances of the two error terms are estimated among other parameters from the data.
It is not surprise, then, that the function with more parameters fits the data better.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com