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CRMSE: combined root mean square error = the square root of [ mean difference between estimated and measured GFR) + (SD of the difference)].
Accuracy was assessed as the percentage of results that did not deviate more than 30% from the measured GFR and also as the combined root mean square error (CRMSE).
Accuracy was expressed by the Combined Root Mean Square Error (CRMSE) calculated as the square root of [ mean difference in estimate-observed)2 + (standard deviation of the difference)].
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Only three indices, which use MERIS red edge and NIR spectral bands (i.e. red edge chlorophyll index, MERIS Terrestrial Chlorophyll Index and red edge NDVI), were found to be able to estimate GPP accurately in both crops combined, with root mean square errors (RMSE) below 3.2 gC/m2/d.
In order to combine multiple values of Fst, we calculated the root mean square of Fst: Fst rms) based on all four comparisons.
We also show that femoral cortex geometry can be predicted from anthropological data combined with femoral measurements with less than 2.3 mm root mean square error, and cortical thickness with less than 0.5 mm root mean square error.
Rq = root mean square roughness.
The root mean square (r.m.s).
(root mean square) and peak displacements, respectively.
A root mean square error of 0.6 °C was obtained.
All models gave similar root mean square error values.
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