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In the deterministic models, the parameter (k_{XG}) is associated with movement from the blood into the environment.
For the Arabidopsis circadian clock models, the parameter sets were given by sequential optimisation strategy against a semi-quantitative (or penalty) cost function [20] and a chi-square cost function [47].
As with many (and perhaps most) other nonlinear models, the parameter space where the minimization of the RMS error is performed, is multidimensional and is characterized by many shallow local minima.
In these first-level models the parameter estimates reflecting signal change for short words vs. fixation baseline (which consisted of the interstimulus interval and the null events), long words vs. fixation, short pseudowords vs. fixation, and long pseudowords vs. fixation were calculated in the context of a GLM [70].
In all models, the parameter <img src="http://journals.plos.org/plosone/article/asset?id=info?doi/10.1371/journal.pone.0017244.e666.PNG" class= inline-graphic"/> in Eq. 11 was optimized even for the No-Constraints models, and codon frequencies were taken to be equal to those in coding sequences.
In linear models, the parameter equals 1.0.
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However, in this model, the parameter estimate is turned around.
Thus, the final model included the parameter days in milk.
The uncertainties in the input parameters into the forward model cause the model parameter error.
However, these models clearly underestimate the parameter.
The utility values used in the model are shown in the model parameter Table 1.
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