Table 2. Root mean square error of one-year ahead predictions (RMSEP) obtained with two different datasets for several statistical models: linear regression (L), quadratic regression (Q), cubic regression (C), dynamic linear models with and without trend (DLMs, DLM0), and Holt-Winters with and without trend (HWs, HW0).
| Models | |||||||||
| Dataset | Quantity | Units | L | Q | C | DLMs | DLM0 | HWs | HW0 |
| France | RMSEP | t ha−1 | 0.82 | 0.76 | 0.70 | 0.71 | 0.68 | 0.71 | 0.68 |
| Differencea | % | 18.73 | 10.49 | 1.77 | 3.40 | 0.09 | 3.98 | 0.00 | |
| Global | RMSEP | t ha−1 | 0.52 | 0.48 | 0.47 | 0.43 | 0.42 | 0.44 | 0.42 |
| Differencea | % | 24.45 | 14.24 | 12.54 | 3.43 | 0.02 | 5.55 | 0.00 | |
a
The differences with respect to the lowest RMSEP values are expressed as a percentage of the lowest RMSEP values (RMSEPmin); Difference = 100*(RMSEP – RMSEPmin)/RMSEPmin.