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One advantage of using multiple species in a single model is that the increased sample size allows better estimation of, and control for, site growing conditions and growing-time differences.
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A single model is developed that can be successfully used in computational simulations of full frontal, offset frontal, side, and oblique car-to-car impacts.
A major advantage of multivariate methods relative to univariate ones is that a single model is used to analyze all variables, and thus, the problems associated with multiple hypothesis testing are absent.
While these conventional methods assume that a single model is locally smooth and consists of topological manifold that contains a large number of meshes, the city model consists chiefly of buildings.
In this paper, we argue that a single model is not sufficient to capture the intra-class variability.
The limitations of external validation of the various predictive models further reinforce the theory that early and late preeclampsia are two distinct disease entities and demonstrate that a single model is unlikely to be an effective predictive tool in all settings.
This is also related to the fact that a single model was not able to capture all desired properties of the weakly adapting model.
The advantage of using a multisphere over a single sphere model is that in the former, each sphere (one per MEG sensor) is fit to a small patch of the head model (directly under the sensor) in order to better model the local return currents.
The limitation of using a single-lag model is that the estimated PM2.5 effect at each of the lag hours could be confounded by the effect of other lag hours.
Substrate polyspecificity indicates that it might be difficult to obtain a single model that is capable of identifying the entire set of BCRP substrates.
A suite is used to overcome bias when using a single model that is attempting to simulate an underlying but unknown model.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com