|
Predictor subset 1 (AIC)
|
Predictor subset 2 (AIC)
|
Minimal AIC
|
P
|
|---|
|
Base (20390.414)
|
subRVIS (20373.159)
|
subRVIS
|
0.0002
|
|
Base (20390.414)
|
subGERP (20370.726)
|
subGERP
|
5.3 × 10–5
|
|
subGERP (20370.726)
|
subRVIS (20373.159)
|
subGERP
|
0.296
|
|
subGERP (20370.726)
|
subRVIS + subGERP (20359.652)
|
subRVIS + subGERP
|
0.004
|
|
subRVIS (20373.159)
|
subRVIS + subGERP (20359.652)
|
subRVIS + subGERP
|
0.001
|
- This table contains the AIC comparisons between different sets of predictors. All models contain the mutation rate as a covariate (Methods). Entries labeled ‘base’ indicate models using only the mutation rate and no other predictors. P is the probability that the model with the larger AIC minimizes the information loss from the model with the lower AIC
