Sentence examples for convergence of model from inspiring English sources

After ensuring the convergence of model parameters, explanations could be given using the estimation results.

What both of these basic approaches have in common is that piecemeal monotonic convergence of model behavior to target system behavior is a mark for confirmation of the model (Koperski 1998).

Finally, the ensemble is used for assessing the reliability of model predictions by defining a measure of convergence of model outputs (consensus) that is used as an indicator of confidence.

Each iteration begins with a near-optimal solution provided by the previous position's estimation, and therefore, the convergence of model fitting is improved and many local minima are naturally avoided.

The V- or U-shaped curves behave very similarly, both with a major minimum at the true parameter value of the reference model, and if multiminimums exist, the major one is much more significant than other smaller ones (also shown in Fig. 3c), which makes the convergence of model inversion much easier, and the inverted parameter values more accurate.

A burn-in of 10% was discarded, and convergence of model parameters was checked with Tracer 1.5 (Rambaut and Drummond 2007).

The contribution of this study to the field of dynamic modeling appears on the convergence of models of heat exchangers, this being accomplished with a variable error in spatial and time minimizing the instabilities in the calculation.

Convergence of models was assessed using all convergence diagnostics in the CODA package [43], in particular cross-correlations and accuracy of estimating quantiles [44].

Logistic regression was used to compare the rate of convergence of models 2 to 8 with model 1 (the model with 4 normal standard distributions).

Even in cases for which we observed some level of convergence of models results, for example, soybean biodiesel, the EC values are considerably higher.

It was not possible to include the covariates "Acute Congestive Heart Failure" and "Cancer" in bivariate and multivariate regression analyses on the cause-specific hazard and sub-distribution hazard of dialysis initiation, because no dialysis events occurred for patients with such characteristics (no convergence of models).