Sentence examples for modelling parameter settings from inspiring English sources

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a Values presented represent range of results generated at all combinations of surrogate CENTURY (Table  4) and CCLUB modelling parameter settings discussed.

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Each point in the description of both models (Sections 1 and 3 of the Methods) contains assumptions, including the Poisson nature of the flows, discrete time, averaging over trajectories with the Monte-Carlo approach, ordering the queue, modeling parameter settings (such as the 9 hrs time period to count transcriptions), etc.

For model parameter selection purposes, the objective function needs to quantify the difference in generalization accuracy when varying the model parameter settings.

Kinetic modeling of brain glucose metabolism in small rodents from positron emission tomography (PET) data using 2-deoxy-2-[18 2-deoxy-2-[18 2-deoxy-2-[18 2-deoxy-2-[18inconsistent, due to different modeling parameter settings and underestimation of the impact of methodological flaws in experimentation.

In simple words, the amplitude equations may offer a guidance for model parameter settings corresponding to specific patterns, e.g., Turing pattern textures.

Using algorithms such as those presented in [ 40], the computational model also facilitates model parameter and structural optimisation, allowing incomplete biological information regarding, for example, model parameter settings and structure, to be established automatically.

We explained in detail the mechanism that, in the full model, enables phenotypic differentiation under random mating and enhances it under assortative mating, focusing on a few typical simulations in which default model parameter settings were used.

Adding social facilitation to the model (parameter settings: Table  1, model b) caused the time that an individual spent near the predator to be positively correlated with that of its companions (model, Spearman rank, r s  = 0.76, N = 64, P = 0.000).

As basic model, we used the avoidance model with parameter settings that result in a coherent group that does not split up (Evers et al. 2011).

We generated multiple realizations of the trait evolution under the different BM and OU models and parameter settings estimated for the four traits.

The best model and parameter settings were chosen according to the Akaike information criterion (AIC) as suggested by Modeltest V3.7 [ 76, 77] for the ML analyses.

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