<!--1-line descr of function--> my.smooth.spline

DESCRIPTION:

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.