fn <- stepfun(x, y, f=0) is.stepfun(fn) knots(fn) plot(fn, ...) print(fn, ...) summary(fn)
x
| numeric vector giving the ``knots'' or jump locations of the step function. |
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.
|
fn
|
an R object inheriting from "stepfun".
|
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
fn(x[i]) = y[i] for i=1,...,n.
The value of the constant c[i] above depends on the
``continuity'' parameter f.
For the default, 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.
"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"; not used, from
approxfun(.)).
The knots are also available by 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 = .2) sfun1 <- stepfun(1:3, y0, f = 1) sfun0 summary(sfun0) summary(sfun.2) 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))