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An alternative approach for modeling these data can be provided by the LW distribution.
Hence when inversely modeling these data, G increases but this has nothing to do with the change in tissue properties [66].
The models with spatial error structures that have been proposed here represent a further improvement in modeling these data, as demonstrated in Table 1.
Our findings suggest that studies using vital signs data to monitor outcomes should consider modeling these data more flexibly, yet efficiently.
For the purpose of modeling these data, explanatory variables were first explored for any associations with the serology result using χ2 test.
An alternative way of modeling these data is to consider a volume fraction-dependent persistence length of polymer brushes and hence a volume fraction-dependent intramolecular correlation function P q, ϕ) as input into Eqs.
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So, the PCNB distribution can be used effectively to model these data.
A normal distribution with a log link function is chosen to model these data.
So, the OLLLW distribution would be a good option to model these data.
Scientists have only now begun to model these data to project future trends, she says.
A parametric Weibull model will be employed to model these data and convert event rates into probabilities.
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