PlotECDF {DescTools} | R Documentation |
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.
PlotECDF(x, breaks = NULL, col = Pal()[1], ylab = "",
lwd = 2, xlab = NULL, ...)
x |
numeric vector of the observations for ecdf. |
breaks |
will be passed directly to |
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. |
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.
no value returned, use plot.ecdf
if any results are required.
Andri Signorell <andri@signorell.net>
PlotECDF(d.pizza$temperature)
# make large vector
x <- rnorm(n=1e7)
# plot only 1000 points instead of 1e7
PlotECDF(x, breaks=1000)