USAGE:
my.smooth.spline(x, y, w, n.orig, df=5., spar=0., cv=F, all.knots=F, df.offset=0., penalty=1.)
REQUIRED ARGUMENTS:
- x
-
Values of the predictor variable.
- y
-
Response variable, of the same length as x.
- w
-
Weights used in the fit.
- n.orig
-
Number of original observations.
- spar
-
Smoothing parameter satisfying spar = (lambda * sigma)/epsiprime/(max(xx) - min(xx))^3.
OPTIONAL ARGUMENTS:
The arguments of my.smooth.spline listed below are in general not used. They are
present because my.smooth.spline is a modified version of smooth.spline.
- df
-
- cv
-
- all.knots
-
- df.offset
-
- penalty
-
VALUE:
This function returns an object of class smooth.spline. See the help of this
function for further details.
REFERENCES:
Eva Cantoni and Elvezio Ronchetti, "Resistant Selection of the Smoothing
Paramater for Smooting Splines", 2001, Statistics and Computing, 11, 141-146.