This model shows a simple example of how to calibrate (or fit) a model to data. The model has parameters C1, k1, k2 and k3 that are optimized to fit a simple 3-exponential function to data stored in a Time Series element.
For each data point, a residual (i.e. data minus model value) is calculated and squared using a Discrete Change Element. The Discrete Change Element triggers at each time point where there is data (in this example at t = 1, 2, 5, 10, 15, 24, 32 and 48 days). Squared residuals calculated by the Discrete Change Element are summed by an Integrator Element to calculated a sum of squared residuals. This is the objective function that is minimized in the optimization by modifying values of C1, k1, k2 and k3. While a simple 3-exponential function is used in this example, any model of arbitrary complexity could be used in place of this function.