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Furthermore, the multivariant method enables to characterize the experimental error, to compare the effects of variables between themselves when variables are normalized, and hence, to gather high-quality information with as few experiments as possible.
We used three continuous error measures (R, inter-quartile range (IQR) of prediction error, the square root of the mean of the squared prediction errors (RMSPE)) and box plot of the precision error to compare the performance of the models.
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We used simulated datasets with varying error rates to compare mapper robustness.
We use 'normalized root mean square error' (NRMSE) to compare regression results.
FS 1.0 based on GPS and LIDAR had a small increase of alignment error to GPS compared to FS 2.0.
When considering the global error metrics, it is convenient to compare the error relative to the quantities being analyzed.
Following these results, we propose a time error index to compare schemes with different degrees of parallelisation.
The calibration curve for tensile force measurement with the new parameter shows a lower prediction error and hysteresis error compared to the time-domain analysis results.
Our analyses showed that orthodontic patients or dental patients might show about 1% to 2% error compared to epidemiological samples, but there seems to be no other choice.
How does ACORN's nationwide error rate compare to other voter registration problems?
Improved outputs from mesoscale models can lead to reduced error compared to real wind speeds in the study area if in situ wind speed measurements are available.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com