predict.smooth.Pspline {pspline} | R Documentation |
Uses an object of class "smooth.Pspline"
to evaluate a polynomial smoothing
spline of arbitrary order or one of its derivatives at new argument values.
predict.smooth.Pspline(splobj, xarg, nderiv=0)
splobj |
a fitted smooth.Pspline object.
|
xarg |
the argument values at which the spline or its derivative is to be evaluated. |
deriv |
the order of the derivative required default is 0, the function itself. |
The method produces results similar to function predict.smooth.spline
, but
the smoothing function is a natural smoothing spline rather than a B-spline
smooth, and the order of the spline can be chosen freely, where order
in this case means the order of the derivative that is penalized.
smooth.spline
penalizes the second derivative, and consequently only
derivatives or order 0 or 1 are useful, but because smooth.Pspline
penalizes a derivative of order m, derivatives up to order m-1 are useful.
The general recommendation is to penalize the derivative two beyond the
highest order derivative to be evaluated.
a list with components xarg
and dy
; the xarg
component is identical
to the input xarg
sequence, the dy
component is the evaluated derivative
of order deriv
.
Heckman, N. and Ramsay, J. O. (1996) Spline smoothing with model based penalties. McGill University, unpublished manuscript.
example(smooth.Pspline) ## smoother line is given by xx <- seq(4, 25, length=100) lines(xx, predict(sm.spline(speed, dist, df=5), xx), col = "red") ## add plots of derivatives lines(xx, 10*predict(sm.spline(speed, dist), xx, 1), col = "blue") lines(xx, 100*predict(sm.spline(speed, dist), xx, 2), col = "green")