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.
the argument values at which the spline or its derivative is to be evaluated.
the order of the derivative required – the default is 0, the function itself.
further arguments passed to or from other methods.
The method produces results similar to function the
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
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
A list with components
component is identical to the input
xarg sequence, the
dy component is the evaluated derivative of order
Heckman, N. and Ramsay, J. O. (1996) Spline smoothing with model based penalties. McGill University, unpublished manuscript.
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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")
smth.P> data(cars) smth.P> attach(cars) smth.P> plot(speed, dist, main = "data(cars) & smoothing splines") smth.P> cars.spl <- sm.spline(speed, dist) smth.P> cars.spl Call: smooth.Pspline(x = ux, y = tmp[, 1], w = tmp[, 2], method = method) Smoothing Parameter (Spar): 366.8429 Equivalent Degrees of Freedom (Df): 2.428851 GCV Criterion: 29.54554 CV Criterion: 39.18787 smth.P> lines(cars.spl, col = "blue") smth.P> lines(sm.spline(speed, dist, df=10), lty=2, col = "red")
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