% File src/library/stats/man/ecdf.Rd % Part of the R package, http://www.R-project.org % Copyright 1995-2007 R Core Development Team % Distributed under GPL 2 or later \name{ecdf} \alias{ecdf} \alias{plot.ecdf} \alias{print.ecdf} \title{Empirical Cumulative Distribution Function} \usage{ ecdf(x) \method{plot}{ecdf}(x, \dots, ylab="Fn(x)", verticals = FALSE, col.01line = "gray70") \method{print}{ecdf}(x, digits= getOption("digits") - 2, \dots) } \arguments{ \item{x}{numeric vector of the observations for \code{ecdf}; for the methods, an object inheriting from class \code{"ecdf"}.} \item{\dots}{arguments to be passed to subsequent methods, i.e., \code{\link{plot.stepfun}} for the \code{plot} method.} \item{ylab}{label for the y-axis.} \item{verticals}{see \code{\link{plot.stepfun}}.} \item{col.01line}{numeric or character specifying the color of the horizontal lines at y = 0 and 1, see \code{\link{colors}}.} \item{digits}{number of significant digits to use, see \code{\link{print}}.} } \description{ Compute or plot an empirical cumulative distribution function. } \details{ The e.c.d.f. (empirical cumulative distribution function) \eqn{F_n}{Fn} is a step function with jumps \eqn{i/n} at observation values, where \eqn{i} is the number of tied observations at that value. Missing values are ignored. For observations \code{x}\eqn{= (}\eqn{x_1,x_2}{x1,x2}, \ldots \eqn{x_n)}{xn)}, \eqn{F_n}{Fn} is the fraction of observations less or equal to \eqn{t}, i.e., \deqn{F_n(t) = \#\{x_i\le t\}\ / n = \frac1 n\sum_{i=1}^n \mathbf{1}_{[x_i \le t]}.}{ Fn(t) = #\{x_i \le t\} / n = 1/n sum(i=1,n) Indicator(xi <= t).} The function \code{plot.ecdf} which implements the \code{\link{plot}} method for \code{ecdf} objects, is implemented via a call to \code{\link{plot.stepfun}}; see its documentation. } \value{ For \code{ecdf}, a function of class \code{"ecdf"}, inheriting from the \code{"\link{stepfun}"} class. } \author{ Martin Maechler, \email{maechler@stat.math.ethz.ch}.\cr Corrections by R-core. } \seealso{\code{\link{stepfun}}, the more general class of step functions, \code{\link{approxfun}} and \code{\link{splinefun}}. } \examples{ ##-- Simple didactical ecdf example: Fn <- ecdf(rnorm(12)) Fn tt <- seq(-2,2, by = 0.1) 12* Fn(tt) # Fn is a 'simple' function {with values k/12} summary(Fn) knots(Fn)# the unique data values {12 of them if there were no ties} y <- round(rnorm(12),1); y[3] <- y[1] Fn12 <- ecdf(y) Fn12 knots(Fn12)# unique values (always less than 12!) summary(Fn12) summary.stepfun(Fn12) ## Advanced: What's inside the function closure? print(ls.Fn12 <- ls(environment(Fn12))) ##[1] "f" "method" "n" "x" "y" "yleft" "yright" utils::ls.str(environment(Fn12)) ###----------------- Plotting -------------------------- require(graphics) op <- par(mfrow=c(3,1), mgp=c(1.5, 0.8,0), mar= .1+c(3,3,2,1)) F10 <- ecdf(rnorm(10)) summary(F10) plot(F10) plot(F10, verticals= TRUE, do.points = FALSE) plot(Fn12 , lwd = 2) ; mtext("lwd = 2", adj=1) xx <- unique(sort(c(seq(-3, 2, length=201), knots(Fn12)))) lines(xx, Fn12(xx), col='blue') abline(v=knots(Fn12),lty=2,col='gray70') plot(xx, Fn12(xx), type='o', cex=.1)#- plot.default {ugly} plot(Fn12, col.hor='red', add= TRUE) #- plot method abline(v=knots(Fn12),lty=2,col='gray70') ## luxury plot plot(Fn12, verticals=TRUE, col.points='blue', col.hor='red', col.vert='bisque') ##-- this works too (automatic call to ecdf(.)): plot.ecdf(rnorm(24)) title("via simple plot.ecdf(x)", adj=1) par(op) } \keyword{dplot} \keyword{hplot}