R: Empirical Cumulative Distribution Function

PlotECDF {DescTools} | R Documentation

## Empirical Cumulative Distribution Function

### Description

Faster alternative for plotting the empirical cumulative distribution function (ecdf). The function offers the option to construct the ecdf on the base of a histogram, which makes sense, when x is large. So the plot process is much faster, without loosing much precision in the details.

### Usage

    PlotECDF(x, breaks = NULL, col = Pal()[1], ylab = "",
             lwd = 2, xlab = NULL, ...)

### Arguments

`x` | numeric vector of the observations for ecdf.
`breaks` | will be passed directly to `hist`. If left to `NULL`, no histogram will be used.
`col` | color of the line.
`ylab` | label for the y-axis.
`lwd` | line width.
`xlab` | label for the x-axis.
`...` | arguments to be passed to subsequent functions.

### Details

The stats function `plot.ecdf` is fine for vectors that are not too large. However for n ~ 1e7 we would observe a dramatic performance breakdown (possibly in combination with the use of `do.call`).

`PlotECDF` is designed as alternative for quicker plotting the ecdf for larger vectors. If `breaks` are provided as argument, a histogram with that number of breaks will be calculated and the ecdf will use those frequencies instead of respecting every single point.
Note that a plot will rarely need more than ~1'000 points on x to have a sufficient resolution on usual terms. `PlotFdist` will also use this number of breaks by default.

### Value

no value returned, use `plot.ecdf` if any results are required.

### Author(s)

Andri Signorell <andri@signorell.net>

### See Also

`plot.ecdf`, `PlotFdist`

### Examples

    PlotECDF(d.pizza$temperature)

    # make large vector
    x <- rnorm(n=1e7)

    # plot only 1000 points instead of 1e7
    PlotECDF(x, breaks=1000)

[Package DescTools version 0.99.38 Index]