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Overall, the above inversion results are obviously affected by the model settings.
Our analyses on simulated data sets show that the power of the Bayes factor test (BF) in finding the correct model is generally very high and not particularly affected by the model settings.
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We start the evaluation of the model settings by addressing the most prominent question of how many AS signals are we able to identify in the data.
Comparing the marginal likelihood values by two different model settings (optimal substitution models and GTR + G model), most of the Bayes factor results showed that the datasets based on the best-fit models had better performance than those based on the GTR + G model.
In the tab Model Settings you can zoom into the models in this view by clicking the icon Zoom Tray, and selecting Zoom Selected Object.
Mentoring and monitoring students efforts during the development by implementing proposed model with specific model settings introduces controlled cooperation with high clarity in evaluation of individual students work.
The anti-tumor activity of MVA-BN®-HER2 was further evaluated by monitoring mouse survival in two different model settings.
Where baseline risk factors required by the model were not reported in the validation studies we used the Cardiff Model's default settings, drawn from UKPDS 82 [ 30].
Swiss TPH model parameters were estimated by fitting the model to field data from a variety of settings across sub-Saharan Africa [ 31].
The substitution model was defined by the default settings with two exceptions: in the first analysis substitution rates were set to 'invgamma', and in a second analysis, a covarion model [ 48, 49] was applied to assess the effect of coevolving sites on the estimation process.
The model can be contextualized to the local situation by adapting the key steps of the model to the local settings.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com