Sentence examples for large empirical data from inspiring English sources

Plausibility: by examining large empirical data sets to find states that are observed in the population for which the value set is being developed.

Despite the availability of large empirical data sets and the long history of traffic modeling, the theory of traffic congestion on freeways is still highly controversial.

Bagust [11] attempted to build a valuation subset using a set of four explicit quantifiable criteria: 1. Plausibility: by examining large empirical data sets to find states that are observed in the population for which the value set is being developed.

A related approach is to subsample (jackknife) large empirical data sets to determine the minimum amount of data that would have been necessary to recover well-supported trees.

It is proposed here that the most practical proxy measure for distinguishing plausible from 'probably implausible' states is through the analysis of large empirical data sets from survey responses obtained from different patient or resident populations.

However, comparing a candidate gene to a large empirical control data set collected in the same way can provide evidence for selection that is more reliable than these comparisons with theoretical expectations (22, 54, 55).

However, despite the inherent difficulties of obtaining fine-scale movement behaviour of large predators, empirical data is needed to complement other data sources such as dietary information and prey abundance, and to supplement predator-prey modelling studies [61].

However, bootstrapping requires access to - preferably large - empirical data sets that can be used to represent the distributions of necessary variables.

The two moderately informative models are structurally based on the unrestricted heterogeneous variance model and the variance priors are either frequentistic distribution approximations from within the MTC data or distributions previously derived from a large external empirical data set.

While significant advances have been made in technical aspects of the AFLP methodology, theoretical studies investigating methods for optimizing the cDNA-AFLP screens remain relatively rare, and large scale empirical data - as provided here for eukaryotes - have not yet been used for this purpose [ 6- 8].

Fortunately, there exists a large amount of empirical data, obtained from thousands of thermodynamic experiments, that, when supported by theoretical principles, allows steelmakers to predict such temperature changes.