approxfun {stats} | R Documentation |
Return a list of points which linearly interpolate given data points, or a function performing the linear (or constant) interpolation.
approx (x, y = NULL, xout, method = "linear", n = 50, yleft, yright, rule = 1, f = 0, ties = mean) approxfun(x, y = NULL, method = "linear", yleft, yright, rule = 1, f = 0, ties = mean)
x, y |
numeric vectors giving the coordinates of the points to be
interpolated. Alternatively a single plotting structure can be
specified: see |
xout |
an optional set of numeric values specifying where interpolation is to take place. |
method |
specifies the interpolation method to be used. Choices
are |
n |
If |
yleft |
the value to be returned when input |
yright |
the value to be returned when input |
rule |
an integer (of length 1 or 2) describing how interpolation
is to take place outside the interval [ |
f |
for |
ties |
Handling of tied |
The inputs can contain missing values which are deleted, so at least
two complete (x, y)
pairs are required (for method =
"linear"
, one otherwise). If there are duplicated (tied) x
values and ties
is a function it is applied to the y
values for each distinct x
value.
Useful functions in this context include mean
,
min
, and max
. If ties = "ordered"
the x
values are assumed to be already ordered. The first
y
value will be used for interpolation to the left and the last
one for interpolation to the right.
approx
returns a list with components x
and y
,
containing n
coordinates which interpolate the given data
points according to the method
(and rule
) desired.
The function approxfun
returns a function performing (linear or
constant) interpolation of the given data points. For a given set of
x
values, this function will return the corresponding
interpolated values. It uses data stored in its environment when it
was created, the details of which are subject to change.
The value returned by approxfun
contains references to the code
in the current version of R: it is not intended to be saved and
loaded into a different R session. This is safer for R >= 3.0.0.
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.
spline
and splinefun
for spline
interpolation.
require(graphics) x <- 1:10 y <- rnorm(10) par(mfrow = c(2,1)) plot(x, y, main = "approx(.) and approxfun(.)") points(approx(x, y), col = 2, pch = "*") points(approx(x, y, method = "constant"), col = 4, pch = "*") f <- approxfun(x, y) curve(f(x), 0, 11, col = "green2") points(x, y) is.function(fc <- approxfun(x, y, method = "const")) # TRUE curve(fc(x), 0, 10, col = "darkblue", add = TRUE) ## different extrapolation on left and right side : plot(approxfun(x, y, rule = 2:1), 0, 11, col = "tomato", add = TRUE, lty = 3, lwd = 2) ## Show treatment of 'ties' : x <- c(2,2:4,4,4,5,5,7,7,7) y <- c(1:6, 5:4, 3:1) approx(x, y, xout = x)$y # warning (ay <- approx(x, y, xout = x, ties = "ordered")$y) stopifnot(ay == c(2,2,3,6,6,6,4,4,1,1,1)) approx(x, y, xout = x, ties = min)$y approx(x, y, xout = x, ties = max)$y