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The models being compared here are a DDM with variability in drift rate44, 47 and an UGM that incorporates variability in drift rate and an urgency signal44.
Moreover the advantages and design limitations of the new DTI are investigated by TCAD simulations and analytical models, being compared to its DTI predecessor in a Nepi/BLN/P−/P+ stack.
Designs are proposed in which different periods of record from within each watershed are used to calibrate (or validate) each of the models being compared; subject to the random allocation of models to test periods, the designs provide a valid measure of the uncertainty in measures of model performance.
LR is a chi-square based statistical test and it is measured as the difference between deviances for the two IRT models being compared.
However, model comparison in a Bayesian framework can be achieved by calculating the Bayes Factor (BF), which is the ratio of the marginal likelihoods with respect to the prior of the two models being compared [38].
Model comparison in a Bayesian framework can be achieved, however, by calculating the Bayes Factor (BF), which is the ratio of the marginal likelihoods (marginal with respect to the prior) of the two models being compared [39].
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Models were compared using Akaike information criterion (AIC).
A total of eight candidate models were compared using the package MuMIn in R (v 1.15.6 57.
The performances of different models were compared.
The models were compared using the Deviance Information Criterion.
The two numerical models were compared.
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