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A model can be studied in state space by following its trajectory from the initial state to some chosen final state.
It was set to 0.5 during training, but the influence of this parameter on the performance of the final model can be studied by a Receiver Operating Characteristic (ROC) threshold test [32].
With respect to Method 2, Method 1 has the advantage of allowing the use of various discrepancy functions whereas Method 2 requires very specific test statistic functions; this means that different aspects of the probabilistic model can be studied with Method 1 rather than only the t functions that characterize the hypothesized probabilistic distribution.
This 'optimism' of the original model can be studied with internal validation techniques [ 10].
Now this meta-network model can be studied in relation to the data it was generated from--for example, different modules described in different data tables in relation to each other--and in relation to the other integrated data.
By analyzing the transition matrix, both the "short term" transient behavior and the "long term" limiting behavior of the model can be studied, thus putting the matrix at the center of attention for the biological interpretation of the results.
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The geometric approach applied to host-vector models can be studied in [7, 8].
Using this technology, neuronal cell models can be studied in the context of the same genetic background of the patient.
Indices of DM cardiac autonomic neuropathy in animal models can be studied by a variety of methods, including analysis of myocardial NE content, cardiac sympathetic and parasympathetic innervation density, and heart rate variability [ 37].
This description must be systematic; the result will be a 'data model', which can be studied to discern patterns in the phenomena.
The strength of structural change over the transitional period in Model 3 can be studied as follows.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com