Sentence examples for model assignment of from inspiring English sources

This should integrate over the distribution of unknown stimulus values <img src="http://journals.plos.org/plosone/article/asset?id=info?doi/10.1371/journal.pone.0004205.e060.PNG" class= inline-graphic"/> (since subjects are not directly asked about these) in determining the most plausible model (assignment of oddity).

Each iteration of a model assignment (both within a semester and among semesters) emphasized scaffolding of model mastery, modeling process development, and development of the cooperative process.

They are then usually assigned to the class for which they have the highest probability of membership (model assignment).

Further refinement of the model will address several issues, including conservatism in the transport model, the assignment of parameters in the flow and transport models, and the underlying assumptions used to support the conceptual models of flow and transport in the unsaturated zone at Yucca Mountain.

We have conducted simulation studies based around realistic parameter values of situations where a putative patient-level variable is being considered for inclusion in an EU model and/or the mechanistic interpretation from the sub-model assignment is of interest.

She had set up a blog advertising her availability for appearances and modelling assignments to make use of her new-found notoriety.

Measurement of attributes within these models allows assignment of utility scores based on population models of values summarized by the index; however, if these measures were not performed during the study, the direct application of a health index model is not possible.

A (symmetrical) probability on L 3) thus induces a normal measure on sets of models: Any assignment of non-negative numbers summing to one to the state descriptions or models fixes probabilities.

The finite element models allow assignment of a wide range of elastic plastic properties to the sample while circumventing many of the uncertainties faced in experimental investigations, and thereby offer unique opportunities for critical validation of the different data analysis procedures.

Accordingly, we need full quantitative predictions from the model, and this can be achieved only after the model's calibration (assignment of specific parameter values) and numerical solution (as dynamic stochastic models have no closed-form solutions).

For model building the information criteria can be used, but large differences are required (⪆6) to provide reasonable evidence of sub-model assignment.