hist.bxp(x, nclass, breaks, probability=FALSE, include.lowest=TRUE,
xlab = deparse(substitute(x)),
...,
width=0.2, boxcol=3, medcol=0, medlwd=5, whisklty=2, staplelty=1)
NA
s) are allowed.x
.sum(breaks[i] < x <= breaks[i+1])<="" code="">
except that if include.lowest
is TRUE
(the default),
the first bar also includes po=>
TRUE
, the histogram will be scaled as a probability
density; the sum of the bar heights times bar widths will equal 1
. If
FALSE
, the heights of the bars will be counts.TRUE
(the default), the lowest bar will include data
points equal to the lowest break, otherwise it will act like the
other bars (see the description of the breaks
argument).0.2
.0
can be used to
designate filling with the background color. The default is to fill
with color 3
.NA
,
indicates the current plotting color (par("col")
). The
default is 0
(the background color). If boxcol=0
and
medcol
is not expNA
, is used to indicate
the current line width (par("lwd")
). The default is 5
.NA
indicates the
current line type (par("lty")
). The default is 2
(dotted line).NA
indicates the current line type (par("lty")
). The default is
1
(solid line). Graphical parameters (see par
include.lowest
is FALSE
the bottom breakpoint must be
strictly less than the minimum of the data, otherwise (the default) it
must be less than or equal to the minimum of the data. The top
breakpoint must be greater than or equal to the maximum of the data.hist
, barplot
,
boxplot
, rug
and
scat1d
in the lab <- "50 samples from a t distribution with 5 d.f."
mult.fig(2*3, main = "Hist() + Rug() and Hist.bxp(*)")
for(i in 1:3) {
my.sample <- rt(50, 5)
hist(my.sample, main=lab); rug(my.sample)# for 50 obs., this is ok, too..
hist.bxp(my.sample, main=lab)
}
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