Spline Smoother Dialog Function

DESCRIPTION:

This function is used by the Spline Smoother dialog.

USAGE:

menuSmooth.spline(data=NULL, x, y, w, df, spar=0, cv, all.knots=F,  
                  df.offset=0, penalty=1, plot.curve=T) 

REQUIRED ARGUMENTS:

x
a vector containing values of the predictor variable. There should be at least 10 distinct x values.

OPTIONAL ARGUMENTS:

data
an optional data frame in which to interpret the x and y variables.
y
a vector containing values of the response variable., of the same length as x.
w
vector of weights for weighted smoothing, of the same length as x and y.
df
a number which supplies the degrees of freedom = trace(S) rather than a smoothing parameter. Here S is the implicit smoother matrix. If both df and spar are supplied, spar is used unless it is 0, in which case df is used.
spar
the coefficient of the integrated second squared derivative penalty function (commonly denoted by lambda) for normalized data. If spar is 0 or missing and df is missing, cross-validation is used to automatically select spar. If a value of spar greater than 0 is supplied, it is used as the smoothing parameter.
cv
indicates whether the "ordinary" or "generalized" cross-validation score should be computed.
all.knots
if FALSE, a suitable fine grid of knots is chosen, usually less in number than the number of unique values of x. If TRUE, the unique values of x are used as knots.
df.offset
allows an offset to be added to the df term used in the calculation of the GCV criterion: df=tr(S)+ df.offset.
penalty
allows the df quantity used in GCV to be charged a cost=penalty per degree of freedom.
plot.curve
if TRUE, a scatterplot with a corresponding smoothing spline is generated.

VALUE:

an object of class smooth.spline. See the smooth.spline help file for details.

SIDE EFFECTS:

A plot will be drawn if requested.

SEE ALSO:

, , .