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As a comparison of the effect on goodness of fit, QQ plots from models fit based on standard Poisson and NB assumptions are provided.
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Figure 6 shows the Renkin-Crone model fits based on three-parameter kinetic model fits using scaled IDIFs; Table 3 gives corresponding parameter estimates.
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.
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.
This obviously shows the need for grid model fitting based on datasets MAM1 and MAM2 when they are not allowed to be pooled.
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.
We propose a statistical method for assessing model fit based on GDDA.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com