multiecdf | R Documentation |
Plot multiple empirical cumulative distribution functions (ecdf)
and densities with a user interface similar to that of boxplot
.
The usefulness of multidensity
is variable, depending on the
data and the smoothing kernel.
multiecdf
will in many cases be preferable. Please see Details.
multiecdf(x, ...)
## S3 method for class 'formula'
multiecdf(formula, data = NULL, xlab, na.action = NULL, ...)
## S3 method for class 'matrix'
multiecdf(x, xlab, ...)
## S3 method for class 'list'
multiecdf(x,
xlim,
col = brewer.pal(9, "Set1"),
main = "ecdf",
xlab,
do.points = FALSE,
subsample = 1000L,
legend = list(
x = "right",
legend = if(is.null(names(x))) paste(seq(along=x)) else names(x),
fill = col),
...)
multidensity(x, ...)
## S3 method for class 'formula'
multidensity(formula, data = NULL, xlab, na.action = NULL, ...)
## S3 method for class 'matrix'
multidensity(x, xlab, ...)
## S3 method for class 'list'
multidensity(x,
bw = "nrd0",
xlim,
ylim,
col = brewer.pal(9, "Set1"),
main = if(length(x)==1) "density" else "densities",
xlab,
lty = 1L,
legend = list(
x = "topright",
legend = if(is.null(names(x))) paste(seq(along=x)) else names(x),
fill = col),
density = NULL,
...)
formula |
a formula, such as |
data |
a data.frame (or list) from which the variables in
|
na.action |
a function which indicates what should happen
when the data contain |
x |
methods exist for: |
bw |
the smoothing bandwidth, see the manual page for
|
xlim |
Range of the x axis. If missing, the data range is used. |
ylim |
Range of the y axis. If missing, the range of the density estimates is used. |
col , lty |
Line colors and line type. |
main |
Plot title. |
xlab |
x-axis label. |
do.points |
logical; if |
subsample |
numeric or logical of length 1. If numeric, and
larger than 0, subsamples of that size are used to compute and plot
the ecdf for those elements of |
legend |
a list of arguments that is passed to the function
|
density |
a list of arguments that is passed to the function
|
... |
Further arguments that get passed to the |
Density estimates: multidensity
uses the function
density
. If the density of the data-generating
process is smooth on the real axis, then the output from this function tends to produce
results that are good approximations of the true density. If,
however, the true density has steps (this is in particular the case
for quantities such as p-values and correlation coefficients, or for
some distributions that have weight only on the posititve numbers, or
only on integer numbers), then
the output of this function tends to be misleading. In that case, please
either use multiecdf
or histograms, or try to improve the
density estimate by setting the density
argument (from
, to
, kernel
).
Bandwidths: the choice of the smoothing bandwidths in multidensity
can be problematic, in particular, if the different groups vary with
respect to range and/or number of data points. If curves look
excessively wiggly or overly smooth, try varying the arguments
xlim
and bw
; note that the argument bw
can be a
vector, in which case it is expect to align with the groups.
For the multidensity
functions, a list of
density
objects.
Wolfgang Huber
boxplot
,
ecdf
,
density
words = strsplit(packageDescription("geneplotter")$Description, " ")[[1]]
factr = factor(sample(words, 2000, replace = TRUE))
x = rnorm(length(factr), mean=as.integer(factr))
multiecdf(x ~ factr)
multidensity(x ~ factr)
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