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We did not perform any model simplification and assessed model fit based on χ2-statistics.
Blue circles in figure 3(a) correspond to each measured resonance position; the solid line is the FDTD model fit based on the dielectric constant as described above (the steps in the theory curve are due to the finite size of the mesh used).
Among the four models that included additional predictors, M2 with form effects indicated the worst model fit, whereas M4 with only significant item position effects indicated the best model fit based on both AIC and BIC.
Confidence intervals were constructed from the best model fit based on the variance of the data, using the "predict" functions in R [30].
Therefore, we also assessed model fit based on calibration plots.
Hence, for assessing the model fit based on GDDA, we propose a new protocol.
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However, our results suggest that a model fitted based on movement data from a single year may not be representative for the overall dispersal rates due to temporal variation in dispersal.
Wake model fits based on short time intervals of length 15sec ≤ T ≤ 10 min within three months of data reveal a strong wake flow variability, resulting in rather broad distributions for the wake expansion parameter.
Figure 6 shows the Renkin-Crone model fits based on three-parameter kinetic model fits using scaled IDIFs; Table 3 gives corresponding parameter estimates.
Both parameters are determined with the CIGALE code which does not only give the best model fitted (based on a χ2 minimization over all the models) but also calculates the probability of each input model and returns the probability distribution function (PDF) of each parameter.
In addition, for all of the constituents, there were better model fits, based on AIC, for UFs than for PM2.5.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com