three variables in the example above.
The relationships between parameter values and variables in the example model are summarized in Table 2.
Let us assume that one of the output variables in the example is [ B *, P, P] which describes both process 2 and process 3. Since none of the three subgraphs depicted in Figure 4C comprises both processes simultaneously the quantity [ B *, P, P] will not be a state of the reduced 22 ODE model. This problem can be overcome by the fusion of two subgraphs.
The most suggestive choice of output variables in this example are the three occurrence levels of the 1st transformation tier, namely [ R EGF, *).*], [ R *, P).*] and [ R. R].
Using the variables in this example, a balloon payment of $89,639.39 will be due at the end of the loan's term.
For example, many variables in the model code were for diagnostic or output purposes and not part of the models functional structure.
Examples of coding of variables in the case vignettes.
In addition to identifying optimal configuration of the design variables, in the last example we also explore whether optimizing the kinetic parameters of specific elements within a given circuit can improve its performance.
Thus, if we set the value of the exogenous variable A in the example above at its default value 0 instead of its actual value 1, we can see that the scenario described above will evolve in the following way: the assassin doesn't put the poison in the coffee, the bodyguard doesn't put the antidote into the coffee, and the king survives.
From a theoretic viewpoint one could rightly argue that the requirement is absurd: by asking to include these variables among the arguments of the policy it implicitly affirms that they are state variables (in the two previous examples they describe the weather system or the catchment), but at the same time it does not intend to model them as such.
