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The R was determined for finding the best models by measuring the amount of the reduction in the variability of response which represses variables in the model and must be close to 1.
In designed experiments, R 2 is a measure of the amount of reduction in the variability of the response obtained using the independent variables in the model.
R2 is a measure of the amount of the reduction in the variability of response obtained by using the repressor variables in the model.
Thus, averaging the decay-corrected calibration source activity measurements resulted in a 23% reduction in the variability of the calibration factor.
In this context, consistency implies obtaining consistent results for the same problem, reliability implies a reduction in the variability in the results while practicality implies the completion of the process with lesser effort.
The uncertainty associated with both response components suggests a need for further improvement in the modeling of wind-structure interaction, prediction of natural frequencies and damping, and reduction in the variability of extreme wind estimates.
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R2 is a measure of the reduction amount in the variability of the response obtained by the independent factor variables in the model.
This work introduces a novel methodology to quantify the profit gain due to reduction in the product variability.
The obtained results confirm that the reduction in the aleatory variability becomes significant beyond T = 0.1 s and for PGV as well (Table 3).
This process is called a genetic drift and can lead to a substantial reduction in the genetic variability within the reared population.
In this way, it has been observed (e.g. Borcherdt 1994) that V S30 is a useful parameter to predict local site amplification in active tectonic regimes, especially when it is actually measured: Derras et al. (2016) showed after Chiou and Young (2008) that measuring V S30 allows a significant reduction in the aleatory variability.
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