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GWR models make great improvements of model performance over OLS models, which is proved by F-test and comparisons of model R2 and corrected Akaike Information Criterion (AICc) from both GWR and OLS.
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The improvement of model performance obtained with an automatic calibration process is also investigated.
The result showed improvement of model performance: compared with PLS model, the root mean square errors of prediction (RMSEP) of iPLS model decreased from 0.111 mg to 0.068 mg, and the R2 parameter increased from 0.9434 to 0.9801.
Here, fitting only the macropore fraction of the bimodal model as immediately drainable additional pore space seems to be a practical approach to account for the macropore effect, as the fitting of the full bimodal model led to only marginal further improvement of model performance.
For further improvement of model performance and model calibration, more trial data and data testing are required here.
For further improvement of model performance and model calibration, more trial data and data testing are required for these crops.
Several studies have shown that the overall, sequential improvement of model performance decreases as more and more variables are added [ 23, 24].
Furthermore, spatial variability of moisture distribution alone is insufficient to explain the observed patterns of model performance improvement.
For catchments with low moisture homogeneity (IM < 80%), IM is a better predictor of model performance improvement than ITV; whereas for catchments with high moisture homogeneity (IM > 80%), ITV is a better predictor of performance improvement than IM.
The net reclassification improvement (93.1%; 95% CI, 91.6%-94.6%; P <.001) and integrated discrimination improvement (15.0%; 95% CI, 14.6%-15.3%; P <.001) indexes both demonstrated significant enhancement of model performance after the addition of NIHSS.
Model selection criteria examples and comparison of model performance statistics.
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CEO of Professional Science Editing for Scientists @ prosciediting.com