
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
$i=1, \dots, n$. 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 from the right,
limits from the left, so that the function is piecewise constant on
intervals that include their left endpoint.
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 left-continuous (i.e., constant
pieces contain their right endpoint).
stepfun(x, y, f = as.numeric(right), ties = "ordered", right = FALSE)
is.stepfun(x)
knots(Fn, ...)
as.stepfun(x, ...)
"print"(x, digits = getOption("digits") - 2, ...)
"summary"(object, ...)
stepfun()
. For the other functions, x
is
as object
below.x
, giving the heights of
the function values between the x values.approxfun
.x
values. Either a function or
the string "ordered"
. See approxfun
."stepfun"
.print
."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;
== "constant"
, from
approxfun(.)
).knots(fn)
.
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 = 0.2)
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
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