Use the options in the Models submenu in the Functional Data Explorer red triangle menu to fit models to your data. See Models for the available models. Each time you fit a different type of model to the data, a model report appears. Each model report contains the following reports:

After you specify the model controls, click Go to view the updated models in the Model Selection report.

Tip: To specify the Model Controls prior to fitting a model, hold down the Shift key and select the desired model from the Functional Data Explorer red triangle menu. See Models.

The Model Selection report contains a solution path plot, an overall prediction plot, and a grid of individual prediction plots for each level of the ID variable. The solution path plot shows a model selection criterion plotted over values of a model parameter. The Bayesian Information Criterion (BIC) is the default fitting criterion. See Model Report Options. For B-Spline and P-Spline models, there is a separate curve in the solution path for each spline degree plotted across the defined number of knots. For Fourier Basis models, the solution path is plotted across the number of Fourier pairs.

The prediction plots show the raw data and prediction curves that correspond to the current model. For spline models, the default model selected is the degree of spline with the best fit. Click on a specific spline in the solution path plot to change the current model selection. The curve in the overall prediction plot is a prediction of the mean. The curves in the individual prediction plots are prediction curves for each specific function. For B-Spline models, the overall prediction plot also displays the location of the knots. You can change the location of the knots by dragging the blue slider bars to different locations. To update the model reports according to the new knot locations, click the Update Models button. To reset the knots to their default locations, click the Reset Knots button.

Displays the -2 Log Likelihood, the values for the AICc, BIC, and GCV model fitting criterion, and a value for <Y, Output> Std Dev. <Y, Output> Std Dev is the residual sigma from the fitted model. When a P-Spline model is selected, the penalty parameter λ is also displayed.

Tip: If you have multiple functional processes, you can customize all Function Summaries reports to show the same summary values by clicking Ctrl and selecting Customize Function Summaries.