spline[fun] {base}

R Documentation

Interpolating Splines

Description

spline performs cubic spline interpolation of the given data points. It returns a list containing components x and y which give the ordinates where interpolation took place and the interpolated values.

splinefun returns a function which will perform cubic spline interpolation of the given data points. This is often more useful than spline.

If method="fmm", the spline used is that of Forsythe, Malcolm and Moler (an exact cubic is fitted through the four points at each end of the data, and this is used to determine the end conditions). Natural splines are used when method="natural", and periodic splines when method="periodic".

Usage

splinefun(x, y, method = "fmm")
spline(x, y, n = 3*length(x), method = "fmm",
       xmin = min(x), xmax = max(x))

Arguments

x, y	vectors giving the coordinates of the points to be interpolated. Alternatively a single plotting structure can be specified.
method	specifies the type of spline to be used. Possible values are "fmm", "natural" and "periodic".
n	interpolation takes place at n equally spaced points spanning the interval [xmin, xmax].
xmin	left-hand endpoint of the interpolation interval.
xmax	right-hand endpoint of the interpolation interval.

References

Forsythe, G. E., M. A. Malcolm and C. B. Moler (1977). Computer Methods for Mathematical Computations.

See Also

approx and approxfun for constant and linear interpolation.

Examples

x <- 1:10
y <- rnorm(10)
op <- par(mfrow = c(2,1), mgp = c(2,.8,0), mar = .1+c(3,3,3,1))
plot(x, y, main = "spline[fun](.) through 10 points")
lines(spline(x, y))
lines(spline(x, y, n = 201), col = 2)

f <- splinefun(x, y)
ls(envir = environment(f))
splinecoef <- eval(expression(z), envir = environment(f))
curve(f(x), 1, 10, col = "green", lwd = 1.5)
points(splinecoef, col = "purple", cex = 2)
par(op)

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