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Table 3 summarizes the results obtained from the model comparisons on the Fujisaki accent level parameters, viz.
Table 2 summarizes the results obtained from the model comparisons on the Fujisaki phrase level parameters, that is, phrase command magnitude Ap and phrase duration, the distance between subsequent phrase commands.
An alternative approach is to resample from the posterior distributions to obtain a statistical ensemble of model parameters and base model comparisons on that ensemble.
In this work, we have introduced a parallelization of the model-switch integration method, as proposed by Lartillot and Philippe [ 18], to accurately calculate Bayes Factors for model comparisons on large datasets.
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First, we conducted a model comparison on ten chronograms using the CoMET model with a constant rate birth-death process implemented in the TESS 2.1.0.
The computation is as described for model comparison on simulated data.
As observed in table 2, the model comparison on the simulated data selects the proper mechanism in all cases.
We conclude on the generality of our graphical method for model comparison, on its limits with respect to the representation of the structure of the interactions in SBML, and on some perspectives for dealing with the dynamics.
Although the described process was based on a manual reconciliation of the two models, the authors suggest a workflow that should be amenable to a degree of automation and might provide a first step on the path towards full multi-model comparisons on a metabolic network level.
However, there are very few reports on model comparisons based on real data from livestock [ 27, 28].
A zero-inflation parameter was included when indicated by model comparisons based on AIC.
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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