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Although the pseudo first- and second-order models are easier to use for data analysis, the resultant model parameters depend on operating conditions.
When taken separately (using human cognition), these models are easier to read and write, and when taken together (using automation), they increase awareness of the possible behaviors that are latent in a design, so that many more use cases can be exposed.
At that, some models are easier to keep running than others.
The performance based AdWords and AdSense models are easier to measure and appeals to the logical / analytical minds at Google.
Such cohort models are easier and less resource-intensive to construct than individual-level models, but suffer from a number of limitations.
On the other hand, an advantage is that discrete-time models are easier to analyse than continuous-time ones, and then the effectiveness of a potential treatment to eradicate the disease from the host population can be easier to derive.
Similar(45)
Nevertheless, these models are easy to unify with inflation.
The parameters in the models are easy to determine and have a well-defined physical significance.
The models are easy to use and appropriate for a wide range of experimental designs.
Four application examples demonstrate that the models are easy-to-use design tools for structural engineers.
The models are easy and inexpensive to construct, and their design and implementation in the session is described here.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com