This model illustrates how to fit a trend line to data using the Gauss-Newton method. This allows you to estimate trend line parameters that can be useful in forecasting. The implementation uses a Looping Container to carry out the required iterative calculations. The Looping Container is conditionally activated right at the beginning of the simulation and then deactivates after the first time step.
Note that the Gauss-Newton method requires that you have a specific equation you want to fit to data. If you have a complex model for which you need to estimate optimal input parameters, you should use GoldSim's optimization capabilities. But when you want to fit a known equation to a data set, the Gauss-Newton method is much more efficient.
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I updated the model to include an embedded chart on the dashboard (2/13/2019)
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