Renext (version 3.1-4)

expplot: Classical "exponential distribution" plot

Description

Plot a vector using "exponential distribution" scales

Usage

expplot(x,
        plot.pos = "exp",
        rate = NULL,
        labels = NULL,
        mono = TRUE,
        ...)

Arguments

x

The vector to be plotted.

plot.pos

Plotting position for points: either "exp" for expected ranks or "med" for a median rank approximation (see Details below).

rate

Rate parameter for one or several "exponential distribution" lines to be plotted

labels

Text to display in legend when "exponential distribution" lines are specified

mono

Monochrome graph?

...

Arguments to be passed to plot.

Author

Yves Deville

Details

This plot shows \(-\log[1-F(x)]\) against \(x\) where \(F(x)\) at point \(i\) is taken as \(i/(n+1)\) if plot.pos is "exp", or as the "median rank" approximation \((i-0.3)/(n+0.4)\) if plot.pos is "med".

If the data in x is a sample from an exponential distribution, the points should be roughly aligned. However the largest order statistics have high sampling dispersion.

See Also

The weibplot function for a classical "Weibull" plot. The interevt is useful to compute interevents (or "interarrivals") that should follow an exponential distribution in the homogeneous Poisson process context.

Examples

 x <- rexp(200)
 expplot(x, rate = 1/mean(x), labels = "fitted")