% File src/library/stats/man/stepfun.Rd % Part of the R package, https://www.R-project.org % Copyright 1995-2014 R Core Team % Distributed under GPL 2 or later \name{stepfun} \title{Step Functions - Creation and Class} \alias{stepfun} \alias{is.stepfun} \alias{as.stepfun} \alias{print.stepfun} \alias{summary.stepfun} \alias{knots} \usage{ stepfun(x, y, f = as.numeric(right), ties = "ordered", right = FALSE) is.stepfun(x) knots(Fn, \dots) as.stepfun(x, \dots) \method{print}{stepfun}(x, digits = getOption("digits") - 2, \dots) \method{summary}{stepfun}(object, \dots) } \arguments{ \item{x}{numeric vector giving the knots or jump locations of the step function for \code{stepfun()}. For the other functions, \code{x} is as \code{object} below.} \item{y}{numeric vector one longer than \code{x}, giving the heights of the function values \emph{between} the x values.} \item{f}{a number between 0 and 1, indicating how interpolation outside the given x values should happen. See \code{\link{approxfun}}.} \item{ties}{Handling of tied \code{x} values. Either a function or the string \code{"ordered"}. See \code{\link{approxfun}}.} \item{right}{logical, indicating if the intervals should be closed on the right (and open on the left) or vice versa.} \item{Fn, object}{an \R object inheriting from \code{"stepfun"}.} \item{digits}{number of significant digits to use, see \code{\link{print}}.} \item{\dots}{potentially further arguments (required by the generic).} } \description{ Given the vectors \eqn{(x_1, \ldots, x_n)}{(x[1], \dots, x[n])} and \eqn{(y_0,y_1,\ldots, y_n)}{(y[0], y[1], \dots, y[n])} (one value more!), \code{stepfun(x, y, \dots)} returns an interpolating \sQuote{step} function, say \code{fn}. I.e., \eqn{fn(t) = c}\eqn{_i}{[i]} (constant) for \eqn{t \in (x_i, x_{i+1})}{t in ( x[i], x[i+1])} and at the abscissa values, if (by default) \code{right = FALSE}, \eqn{fn(x_i) = y_i}{fn(x[i]) = y[i]} and for \code{right = TRUE}, \eqn{fn(x_i) = y_{i-1}}{fn(x[i]) = y[i-1]}, for \eqn{i=1,\ldots,n}{i=1, \dots, n}. The value of the constant \eqn{c_i}{c[i]} above depends on the \sQuote{continuity} parameter \code{f}. For the default, \code{right = FALSE, f = 0}, \code{fn} is a \emph{cadlag} function, i.e., continuous from the right, limits from the left, so that the function is piecewise constant on intervals that include their \emph{left} endpoint. In general, \eqn{c_i}{c[i]} is interpolated in between the neighbouring \eqn{y} values, \eqn{c_i= (1-f) y_i + f\cdot y_{i+1}}{c[i] = (1-f)*y[i] + f*y[i+1]}. Therefore, for non-0 values of \code{f}, \code{fn} may no longer be a proper step function, since it can be discontinuous from both sides, unless \code{right = TRUE, f = 1} which is left-continuous (i.e., constant pieces contain their right endpoint). } \value{ A function of class \code{"stepfun"}, say \code{fn}. There are methods available for summarizing (\code{"summary(.)"}), representing (\code{"print(.)"}) and plotting (\code{"plot(.)"}, see \code{\link{plot.stepfun}}) \code{"stepfun"} objects. The \code{\link{environment}} of \code{fn} contains all the information needed; \item{"x","y"}{the original arguments} \item{"n"}{number of knots (x values)} \item{"f"}{continuity parameter} \item{"yleft", "yright"}{the function values \emph{outside} the knots} \item{"method"}{(always \code{== "constant"}, from \code{\link{approxfun}(.)}).} The knots are also available via \code{\link{knots}(fn)}. } \author{ Martin Maechler, \email{maechler@stat.math.ethz.ch} with some basic code from Thomas Lumley. } \note{ The objects of class \code{"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 \preformatted{ eval(attr(old_obj, "call"), environment(old_obj))} since the data used is stored as part of the object's environment. } \seealso{\code{\link{ecdf}} for empirical distribution functions as special step functions and \code{\link{plot.stepfun}} for \emph{plotting} step functions. \code{\link{approxfun}} and \code{\link{splinefun}}. } \examples{ 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 } \keyword{dplot}