Sentence examples for model assumptions as from inspiring English sources

Exact(10)

For instance, the clear visualisation of logical feedback loops can be easily understood by non-modellers, facilitating dialogue on the model assumptions, as well as allowing a more open and engaging development process.

SS and KB provided critical input into the model assumptions as well as the conceptualization of the referenced research project.

Model assumptions as well as the adopted, idealized profile of occlusion force accumulation are an integral part of research in terms of muscle forces identification.

These sensitivity analyses show the variation in results that might be due to differences in data values and model assumptions, as well as which variables have the largest effect on the results observed.

As will be shown below this turns out to be very useful when constructing confidence regions that are robust to small departures from the model assumptions, as are often encountered in practice.

This software features diagnostic plots that allow one to check the validity of the model assumptions as well as an alternate nonparametric Bayesian method (in case the assumptions for parametric formulation are invalid).

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We are left with environmental stochasticity, or an incorrect simplifying model assumption as potential causes.

Genetic diversity was estimated for the Australian isolates of 936-like phage using both a Watterson estimate (Watterson 1975) assuming infinite sites as implemented in DNAsp ver. 5 (Librado and Rozas 2009) and a modified Watterson estimate that relaxes the infinite sites model assumption as implemented in Pairwise, LDhat 2.5 (Hudson 2001; McVean et al. 2002).

In the reimbursability decision process, an important role is played by both the drug efficacy data observed in pre-licensing RCTs and the economic modelling assumptions, as they give evidence on cost effectiveness.

Calculation methods and model assumptions were as described [ 40- 42].

We describe a systematic approach to evaluating differences in model assumptions and results, as well as differences in modeling culture underlying the differences in model structure and parameters.

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