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Publication date: 04/21/2023

Fit Spline Report

In the Bivariate platform, use the Flexible > Fit Spline option to fit a smoothing spline that varies in smoothness (or flexibility) according to a specified lambda (λ) value. The lambda value is a tuning parameter in the spline formula. Small values of λ place high weight on the model error term for a flexible fit. Large values of λ place low weight on the error term for a stiff fit, approaching a straight line.

Select λ from the Fit Spline menu or select Fit Spline > Other to specify a value for λ. Alternatively, adjust λ interactively in the Smoothing Spline Fit report.

Note: To standardize your X variable, select Fit Spline > Other and select the Standardize X option.

For more information about the options in the Smoothing Spline Fit menu, see Bivariate Fit Options. For statistical details about this fit, see Statistical Details for the Fit Spline Option.

The Smoothing Spline Fit table contains the following columns:

R-Square

The proportion of variation accounted for by the smoothing spline model. See Statistical Details for the Smoothing Fit Report.

Sum of Squares Error

Sum of squared distances from each point to the fitted spline. It is the unexplained error (residual) after fitting the spline model.

Change Lambda

Enables you to change the λ value, either by entering a value, or by moving the slider.

Want more information? Have questions? Get answers in the JMP User Community (community.jmp.com).