The basic underlying model in both cases is a nonlinear network flow model, and we give an overview on the more specific modeling aspects in each case.
If implemented using a general-purpose programming language, the underlying model becomes hidden in the details of the computer code, making it difficult to compare the conceptual and implemented models, and to modify the model.
By placing the model in a container, data scientists can simply adjust the underlying model as needed and relaunch in a continuous delivery kind of approach.
Putting together with equation (2) and equations (5) and (6), one can derive the relationships of J XX, J YY, and J XY with the underlying model parameters (presented in the second column of table 1).
The metric is dependent on the underlying model quality, in such sense PM values around 0.5 are calculated for poor to random models, and values between 0.9 and 1.0 for high quality models.
Smooth supersaturated models are interpolation models in which the underlying model size, and typically the degree, is higher than would normally be used in statistics, but where the extra degrees of freedom are used to make the model smooth using a standard second derivative measure of smoothness.
At each step, we examine the measured signal, estimate the underlying model parameters, and propagate forward in the most consistent direction, which is the principal diffusion direction most aligned with the incoming vector.
Since underlying model assumptions are encoded in the manifold, PEC restricts the application of submodels within its intended use.
When comparing environmental management alternatives, there is a need to assess the effect of uncertainty in the underlying model(s) and future conditions on robustness of recommendations.
