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
- Linear Regression for information on general options and other models
- Options for choosing which results to display
- Further Output for additional output subsequent to analysis
- Saving Results for further analysis
- Fitted Model for graphical display of the model
- Model Checking to generate diagnostic plots for model checking
- MODEL and FIT directives for fitting regression models using the command language
- SSPLINE function for fitting smoothing splines