predict.bSpline {splines} | R Documentation |
Evaluate a Spline at New Values of x
Description
The predict
methods for the classes that inherit from the
virtual classes bSpline
and polySpline
are used to
evaluate the spline or its derivatives. The plot
method for a
spline object first evaluates predict
with the x
argument missing, then plots the resulting xyVector
with
type = "l"
.
Usage
## S3 method for class 'bSpline'
predict(object, x, nseg = 50, deriv = 0, ...)
## S3 method for class 'nbSpline'
predict(object, x, nseg = 50, deriv = 0, ...)
## S3 method for class 'pbSpline'
predict(object, x, nseg = 50, deriv = 0, ...)
## S3 method for class 'npolySpline'
predict(object, x, nseg = 50, deriv = 0, ...)
## S3 method for class 'ppolySpline'
predict(object, x, nseg = 50, deriv = 0, ...)
Arguments
object |
An object that inherits from the |
x |
A numeric vector of |
nseg |
A positive integer giving the number of segments in a set
of equally-spaced |
deriv |
An integer between 0 and |
... |
further arguments passed to or from other methods. |
Value
an xyVector
with components
x |
the supplied or inferred numeric vector of |
y |
the value of the spline (or its |
Author(s)
Douglas Bates and Bill Venables
See Also
xyVector
,
interpSpline
,
periodicSpline
Examples
require(graphics); require(stats)
ispl <- interpSpline( weight ~ height, women )
opar <- par(mfrow = c(2, 2), las = 1)
plot(predict(ispl, nseg = 201), # plots over the range of the knots
main = "Original data with interpolating spline", type = "l",
xlab = "height", ylab = "weight")
points(women$height, women$weight, col = 4)
plot(predict(ispl, nseg = 201, deriv = 1),
main = "First derivative of interpolating spline", type = "l",
xlab = "height", ylab = "weight")
plot(predict(ispl, nseg = 201, deriv = 2),
main = "Second derivative of interpolating spline", type = "l",
xlab = "height", ylab = "weight")
plot(predict(ispl, nseg = 401, deriv = 3),
main = "Third derivative of interpolating spline", type = "l",
xlab = "height", ylab = "weight")
par(opar)