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As expected, the proposed estimators (left (hat alpha ^{text {IQR}}_{2}, ~hat beta ^{text {HL}}right)) and (left (hat alpha ^{text {RC}}_{2}, ~hat beta ^{text {HL}}right)) have some built-in protection against a certain amount of deviation due to data contamination or the measurement errors.
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Table 6 illustrates the precision regarding change in standard deviation due to incomplete data collection.
Indeed, the results at most sites show diagonal elements G xx and G yy close to 1 and off-diagonal elements G xy and G yx close to 0. G xx at OB6 deviates significantly from its expected values; however, E x obs at OB6 shows a number of non-physical spikes; hence, this deviation might be due to data quality.
The average deviation (D_{text{avg}}) for all simulation runs is compared to the reference congestion data from Google Maps Fig. 5 Difference in deviation due to traffic jam avoidance.
This paper proposes a path-tracking algorithm to compensate for path deviation due to torque limits.
Due to data unavailability and when required, standard deviations were assumed to be a 10% of the mean values.
"Due to data limitations..
The dominant refresh strategy reported was daily refresh during nonbusiness hours with some deviations due to operational decision making and data source availability.
This emphasizes patterns in the data by minimizing short-term deviations due to observational errors, such as measurement errors or inherent system noise.
Possible deviations due to residual magnetic field gradients are below the measurement resolution.
The pure marx simulations have much larger deviations due to marx's simplified mirror model.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com