An increase in prediction accuracy may be obtained by grouping predicted entries together to clusters of related sequences.
Overall, the increase in prediction performance was modest and may not outweigh the extra costs of using more detailed covariates.
Basic reasons for such integration are an increase in prediction efficiency and also the necessity to link soil maps to dynamic modelling, enabling risk assessment and impact studies.
The proposed adaptivity of a committee size and aggregation weights led to a statistically significant increase in prediction accuracy if compared to other types of committees.
The co-ordinated nature of the Fifth CMIP (CMIP5 (ref. 23)) near-term ensemble prediction experiments allows, for the first time, obtaining robust estimates of the level of skill of state-of-the-art near-term climate prediction, while taking advantage of the increase in prediction reliability issued by multiple forecast systems in what is known as the multi-model approach4,24.
Model predictive uncertainty increases with the crudity of the bathymetry representation, however, approximations that capture the general shape of the wetland pond such as a power law or Bézier curve show only a small increase in prediction uncertainty compared to the full dGPS surveyed bathymetry, implying these may be sufficient for most modelling purposes.
As the beacon interval is increased, the end-to-end delay increases owing to the increase in prediction inaccuracy as mentioned earlier.
Similar to the SensorScope data, both MC and SS-MC achieve a very stable performance while SS-MC is much less affected by the increase in prediction horizon.
For this specific application of modelling the height-diameter relationship of Norway spruce, we have shown that the implementation of shape constrained smooths ensures a robust biologically meaningful interpretation with only marginal loss of prediction accuracy and no increase in prediction bias.
The increase in prediction accuracy for studies based on larger plots might be attributed to the so-called spatial averaging of the errors, because both the field observations and the ALS data capture more of the spatial variation and are closer to the average value [e.g. 9, 54].
Considering additive × additive epistasis did not produce a sizable increase in prediction accuracy.
