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Although the largest errors are significantly reduced, the updated parameters are believed to be affected by noise from the system identification.
The largest errors are likely biases caused by unmodelled sources (Sabaka et al. 2015) which cannot be assessed using a formal model error covariance matrix, or by constructing models using the same technique from independent datasets.
It highlights two important facts: first, that regions where the model suffers the largest errors are located at high northern (roughly centered on the north geomagnetic pole over Greenland, between 4 and 12 nT) and southern latitudes (up to 4 nT), and second, that errors elsewhere are limited to much lesser values (typically 1 to 2 nT).
Regardless of the method applied, the largest errors are now mostly located in the sinus area and at the bone/dura/CSF boundary.
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The largest errors were in flexion/extension, and least, in axial rotation.
The largest errors were obtained for transfers between debris objects in Sun-Synchronous Orbit (O(100) km error in magnitude of position vector and O 0.1) km/s error in magnitude of velocity vector).
The calibrated model generated a normalized root mean square error (NRMSE) of 21.88% and a mean absolute percentage error (MAPE) of 28.27% for at, where the largest errors were found at 412 nm and 620 nm.
The largest errors were observed for the thresholding techniques (Black et al., Biehl et al., 40% of SUVmax and Nestle et al).
The largest errors were likely mainly due to changes in blood vessel diameter when measuring retinal thicknesses from volumes acquired at different times.
In all n-body calculations, very close approaches of two particles can result in accelerations so large and so rapidly changing that large errors are introduced or the calculation completely diverges.
Moreover, the RMSE is most useful when the large errors are particularly undesirable [34].
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CEO of Professional Science Editing for Scientists @ prosciediting.com