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Smoothing Splines

Select menu: Stats | Regression Analysis | Linear Models

The Smoothing spline option can be selected from the Linear Regression dialog dropdown list.

Smoothing splines are complicated functions, constructed from segments of cubic polynomials between the distinct values of a variate, and constrained to be “smooth” at the junctions. Models that contain splines are no longer linear, but are described as additive models because the effects of separate explanatory variates are still combined additively. The main use of smoothed terms in regression are to investigate the shape relationship with a view to later, parametric fitting, and to remove the effect of nuisance variables so as to concentrate on the variables of interest.

Response variate

Specifies the name of the response (or y-) variate.

Explanatory variate

Specifies the name of the explanatory (or x-) variate.

Degrees of freedom

Specifies the degrees of freedom to control the smoothness. This is effectively increasing or relaxing the constraints.

See also

Updated on March 27, 2019

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