Cubic smoothing spline 
The module Cubic Spline is used to fit any functional regression curve through data with one independent variable x and one dependent random variable y. Number of points (x_{i}, y_{i}) is n. The regression model y = f(x) + ε is composed of p cubic curves defined on p adjacent segments
(∞,x_{u,1})∪<x_{u,1},x_{u,2})∪..∪<x_{u,p1},+∞) of the xaxis separated by p–1 knots. The values x_{u,i} are knots and can be defined by the user. Analytical properties of the curve (like smoothness, curvature, continuity) and statistical properties (residual variance, prediction variance) are subject to modeling.
Cubic smoothing spline  Pdf manual
Output
Dialog window for Cubic spline module
Example output


Last Updated ( 19.03.2013 ) 