Description Usage Arguments Details Value References See Also Examples

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.

1 2 |

`object` |
a fitted |

`xarg` |
the argument values at which the spline or its derivative is to be evaluated. |

`nderiv` |
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 `predict`

method for `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 McGill University, unpublished manuscript.

1 2 3 4 5 6 7 | ```
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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