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To provide a model comparison, we have also studied labour market transitions by applying a traditional parametric MNL model.
The method of model comparison we use consists of comparing the shape and location of the height-integrated conductivity maximum and boundary curves.
For model comparison, we introduce δAIC as: where AICModel is the AIC value of a specific model and AICReference is the AIC value obtained for the Reference Model in which the earthquake potential is homogeneous throughout the Japanese islands.
For the purpose of model comparison, we calculate pseudo R 2, and the out-of-sample pseudo R 2 with bootstrapped confidence intervals by using cross-validation and bootstrap resampling as described above.
In a detailed model comparison, we assessed the model results on consumption, agricultural production, commodity prices, land-use change and greenhouse gas emissions, and identified feedbacks in the global agricultural system.
Lastly, in step 3 for model comparison we use likelihood ratio tests (LRT) rather than AIC.
Similar(40)
In similar model comparisons, we also found no evidence that teacher gesture to equations influenced student encoding of graphs, χ 2 (1) = 0.79, p = .37, and no evidence for an interactive effect of gesture to graphs and gesture to equations, χ 2 (1) = .042, p = .84.84
For model comparisons we used a simulated annealing algorithm to find maximum likelihood parameter sets.
For nested model comparisons, we used the likelihood ratio test as recommended [ 35].
After model comparisons, we used TASSEL package to perform association tests [ 44].
To minimize the impact of this on our EC based model comparisons, we attempted to use KEGG as an "external standard".
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