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However, the VIFs for our models are low, with an average VIF being around 2. As such, multicollinearity is not a large problem in the models.
Solving large-scale, field-wide shale-gas optimization problems put different requirements on the well and reservoir models than conventional history matching, as it is crucial that the models are low ordered, numerically efficient and adaptable to changing operating conditions.
The R2 values of the regression models are low.
Advantages of using in vitro instead of in vivo models are low costs, relatively easy performance, no limitations by ethical constraints, and the possibility to compare different substrates when applying standardized conditions.
The maximum likelihood estimates of λ from our models are low to moderate, between zero and 0.35, for models including both colony size and nest site (Table 2), though the uncertainty in the λ estimates suggests a possibly large phylogenetic signal.
As seen, the rate of xerostomia for plans meeting our developed NTCP models are low, for 43.6 Gy cut-off point, resulting in NPV's of 92% for the SEF data and 95% for the QoL data, and for 44.1 Gy cut-off point, resulting in NPV's of 88.9% for the SEF data and 95.5% for the QoL data, respectively.
Similar(54)
Note that the number of models is low N m = 11.
They predictive power (ability to generate credible predictions) of ln(N t ) and ln(E tT ) models is low based on the adjusted coefficient of determination.
The computational cost of these models is low and they have proven effective in exploring morphodynamic trends and improving our understanding of mesoscale behaviour.
Similarly, for the total protein release, the ANN model was superior to the other models although the R 2 values of all models were low (Table 6, lower panel).
It should be noted that the explained variance of both linear mixed models was low.
Related(20)
examples are low
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models suggest low
models are hard
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