| stepfun {stats} | R Documentation |
Given the vectors (x[1],..., x[n]) and
(y[0],y[1],..., y[n]) (one value
more!), stepfun(x,y,...) returns an interpolating
“step” function, say fn. I.e., fn(t) =
c[i] (constant) for t in (
x[i], x[i+1]) and at the abscissa values, if (by default)
right = FALSE, fn(x[i]) = y[i] and for
right = TRUE, fn(x[i]) = y[i-1], for
i=1,...,n.
The value of the constant c[i] above depends on the
“continuity” parameter f.
For the default, right = FALSE, f = 0,
fn is a “cadlag” function, i.e., continuous at right,
limit (“the point”) at left.
In general, c[i] is interpolated in between the
neighbouring y values,
c[i] = (1-f)*y[i] + f*y[i+1].
Therefore, for non-0 values of f, fn may no longer be a proper
step function, since it can be discontinuous from both sides, unless
right = TRUE, f = 1 which is right-continuous.
stepfun(x, y, f = as.numeric(right), ties = "ordered", right = FALSE)
is.stepfun(x)
knots(Fn, ...)
as.stepfun(x, ...)
## S3 method for class 'stepfun':
print(x, digits = getOption("digits") - 2, ...)
## S3 method for class 'stepfun':
summary(object, ...)
x |
numeric vector giving the knots or jump locations of the step
function for stepfun(). For the other functions, x is
as object below. |
y |
numeric vector one longer than x, giving the heights of
the function values between the x values. |
f |
a number between 0 and 1, indicating how interpolation outside
the given x values should happen. See approxfun. |
ties |
Handling of tied x values. Either a function or
the string "ordered". See approxfun. |
right |
logical, indicating if the intervals should be closed on the right (and open on the left) or vice versa. |
Fn, object |
an R object inheriting from "stepfun". |
digits |
number of significant digits to use, see print. |
... |
potentially further arguments (required by the generic). |
A function of class "stepfun", say fn.
There are methods available for summarizing ("summary(.)"),
representing ("print(.)") and plotting ("plot(.)", see
plot.stepfun) "stepfun" objects.
The environment of fn contains all the
information needed;
"x","y" |
the original arguments |
"n" |
number of knots (x values) |
"f" |
continuity parameter |
"yleft", "yright" |
the function values outside the knots; |
"method" |
(always == "constant", from
approxfun(.)). |
normal-bracket109bracket-normal
The knots are also available by knots(fn).
Martin Maechler, maechler@stat.math.ethz.ch with some basic code from Thomas Lumley.
ecdf for empirical distribution functions as
special step functions and plot.stepfun for plotting
step functions.
y0 <- c(1,2,4,3)
sfun0 <- stepfun(1:3, y0, f = 0)
sfun.2 <- stepfun(1:3, y0, f = .2)
sfun1 <- stepfun(1:3, y0, f = 1)
sfun1c <- stepfun(1:3, y0, right=TRUE)# hence f=1
sfun0
summary(sfun0)
summary(sfun.2)
## look at the internal structure:
unclass(sfun0)
ls(envir = environment(sfun0))
x0 <- seq(0.5,3.5, by = 0.25)
rbind(x=x0, f.f0 = sfun0(x0), f.f02= sfun.2(x0),
f.f1 = sfun1(x0), f.f1c = sfun1c(x0))
## Identities :
stopifnot(identical(y0[-1], sfun0 (1:3)),# right = FALSE
identical(y0[-4], sfun1c(1:3)))# right = TRUE