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We tested for group differences in head motion parameters from image realignment by comparing the framewise displacement and the root mean squared movement (Power et al., 2012; Satterthwaite et al., 2013).
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What was the root mean squared error?
We capture the error created through this process through the root mean squared error (RMSE).
The root mean squared error of calibration (RMSEC) is 0.0503 and the root mean squared error of validation (RMSEV) is 0.0485.
The efficacy of the ANFIS models has been judged through the correlation coefficient (R), mean squared error (MSE) and root mean squared error (RMSE).
Root mean squared error and correlation coefficient were evaluated as performance criteria.
In the former the root mean squared error of prediction (RMSEP) was 0.42 0.50% SOC.
Their root mean squared roughness was in a range from 2 to 6·105 μm.
The root mean squared error was 0.03 mm, which is the effective precision of the method.
The root mean squared error between the measured and simulated changes is ca. s = 0.027 g/cm3.
These parameters minimize the root mean squared error of the model.
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