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The relationship between the two metrics of climate variable importance (percent contribution and permutation importance) was negligible for both the four overfit models (r2 = 0.04) and the two AIC models (r2 = 0.01).
For each analysis, we report in detail the most parsimonious model (the model with the lowest AIC value) and comment the differences with those models within two AIC units – when there were any such models.
The AIC value for the dominant Mendelian model assuming three polygenic loci was the smallest (6413.02) compared to the other models assuming two (AIC = 6441.18) or four (AIC = 6424.61) polygenic loci.
We selected the subset of models within two AIC units of the best model.
AIC close to zero reflects good fit; and between two AIC measures, the lower one reflects the model with the better fit.
The second most parsimonious model, which fell within two AIC values of the most parsimonious model, retained all tested variables (Table 2).
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The analysis showed a best-fit theoretical model of two components (AIC = 374.1; BIC = 383.6) (Additional file 1: Table S1), and a suggested cut-off point at a total score of 4.5.
In contrast, BIC favors one component, except for mitochondrial alignment in which four or six components are virtually indistinguishable (44,416.88 versus 44,416.75), and AIC three or four components.
We will then give the exact threshold expressions of the DED detector using the two selection tools AIC and MDL.
In the model with both additive and interaction effects (model 10), none of the parameters differed significantly from zero and the AIC value (AIC = 24) is almost the same as that of model 6 (AIC = 25).
Assuming that deviations from the translation symmetry in the 2D periodic image are only due to random errors with a Gaussian distribution of mean zero, a geometric AIC is applicable as described in refs. [23, 24].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com