Table 6.
Univariate model set evaluation for A4 background
| Model | Formula | k | RSS | Adjusted R 2 | AICc | Model likelihood | w |
|---|---|---|---|---|---|---|---|
| g01 |
UV index |
3 |
250.36 |
0.52 |
139.76 |
1.00 |
0.68 |
| g05 |
Silt content |
3 |
269.41 |
0.49 |
141.67 |
0.39 |
0.26 |
| g04 |
Atmospheric pressure |
3 |
311.23 |
0.41 |
145.42 |
0.06 |
0.04 |
| g02 |
Mean max. temperature |
3 |
323.71 |
0.39 |
146.44 |
0.04 |
0.02 |
| g06 |
Genetic PC1 |
3 |
430.20 |
0.18 |
153.84 |
0.00 |
0.00 |
| g03 |
Relative humidity |
3 |
454.76 |
0.14 |
155.28 |
0.00 |
0.00 |
| g07 |
Genetic PC2 |
3 |
491.51 |
0.07 |
157.30 |
0.00 |
0.00 |
| g08 | naïve | 2 | 548.85 | 0.00 | 157.60 | 0.00 | 0.00 |
k = number of parameter estimates, RSS = residual sum of squares, AICc = Akaike information criterion adjusted for the sample size, w = conditional model probability (likelihood of model i divided by the sum of model likelihoods).