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The modified criteria allow providing achievement of desirable parameters with smaller expenses of controls power.
As expected, parameters with smaller ICC showed higher SEM values, confirming their poor level of reliability.
Parameters with smaller intra-tumor line heterogeneity had a bigger effect on accuracy; these were in effect the endogenous markers.
Therefore, we propose a stochastic parallel refinement framework to prioritize for those candidate transform parameters with smaller dissimilarity scores.
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The sensitivities of the reliability estimates with respect to model parameters are determined and those parameters with small sensitivity factors are replaced by deterministic values to improve the computational efficiency in the prediction of the ultimate longitudinal strength of ship hull.
However, we believe that parameters with small variances can also reflect speaker characteristics.
The InSAR estimate for this event agrees relatively well with three seismological estimates for all parameters with small uncertainties.
To prove that the sensitivity is a good index for the identifiability, the parameters with small sensitivities, such as E IQmin and D tg, were added into the parameter set for identification.
In some high fitting degree situations, the values of X eq are relative steady, while the values of E IQmin are randomly distributed in its feasible regions, which shows that those parameters with small sensitivities are difficult to be accurately identified.
Overall, the simulation results indicate that when the true model is specified, MPois-Pois or MNB-Pois models estimate marginal mean regression parameters with small biases, Type I errors close to the assumed rate and coverages of 95% confidence intervals near 95% for sample sizes of 200 or greater.
This involved eliminating parameters with small t-values (unless they had practical importance) and adding parameters with large modification indices if they were theoretically sound.
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