Sentence examples for the consequences of models from inspiring English sources

Thus construed, measurement accuracy can be evaluated by establishing robustness among the consequences of models representing different measurement processes.

Among these is the issue of understanding the consequences of model choice itself.

The consequences of model weaknesses are discussed and point towards model improvements.

Moreover, we discuss the consequences of model extensions and additional constraints on process performance.

The significance of process parameters for the most pronounced physical phenomena is discussed as are also the consequences of modelling.

The bias/variance trade off of these estimators is analyzed and the consequences of model misspecification are illustrated.

A measure of model misspecification is proposed, and the consequences of model misspecification in non-experimental causal inference methods are investigated.

Yet the satisfying results for RMSEA and CFI, which consider the consequences of model complexity of the Chi-Square value, deliver strong arguments for the adequacy of the measurement model.

However, the consequences of model computations indicate that the ordinary template assuming an ellipsoidal or a spherical form of cavities for the solute molecules is entirely appropriate for relatively very small and robust molecules, which, at the end, was our principal selection [24, 25, 26, 27].

This paper reviews some recent results on the consequences of model misspecification on the large sample properties of likelihood score tests of association between exposure and response.

In this work we explore the consequences of model choice in eQTL studies reanalyzing public data with maximum likelihood and SVM techniques.