# stepfun

##### Step Functions - Creation and Class

Given the vectors \((x_1, \ldots, x_n)\) and
\((y_0,y_1,\ldots, y_n)\) (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
\(i=1,\ldots,n\).

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,
\(c_i= (1-f) y_i + f\cdot y_{i+1}\).
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).

- Keywords
- dplot

##### Usage

```
stepfun(x, y, f = as.numeric(right), ties = "ordered",
right = FALSE)
```is.stepfun(x)
knots(Fn, …)
as.stepfun(x, …)

# S3 method for stepfun
print(x, digits = getOption("digits") - 2, …)

# S3 method for stepfun
summary(object, …)

##### Arguments

- 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).

##### Value

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;

the original arguments

number of knots (x values)

continuity parameter

the function values *outside* the knots

(always `== "constant"`

, from
`approxfun(.)`

).

##### Note

The objects of class `"stepfun"`

are not intended to be used for
permanent storage and may change structure between versions of R (and
did at R 3.0.0). They can usually be re-created by

eval(attr(old_obj, "call"), environment(old_obj))

since the data used is stored as part of the object's environment.

##### See Also

`ecdf`

for empirical distribution functions as
special step functions and `plot.stepfun`

for *plotting*
step functions.

##### Examples

`library(stats)`

```
# NOT RUN {
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
# }
```

*Documentation reproduced from package stats, version 3.5.0, License: Part of R 3.5.0*