histboxp  R Documentation 
Uses plotly
to draw horizontal spike histograms stratified by
group
, plus the mean (solid dot) and vertical bars for these
quantiles: 0.05 (red, short), 0.25 (blue, medium), 0.50 (black, long),
0.75 (blue, medium), and 0.95 (red, short). The robust dispersion measure
Gini's mean difference and the SD may optionally be added. These are
shown as horizontal lines starting at the minimum value of x
having a length equal to the mean difference or SD. Even when Gini's
and SD are computed, they are not drawn unless the user clicks on their
legend entry.
Spike histograms have the advantage of effectively showing the raw data for both small and huge datasets, and unlike box plots allow multimodality to be easily seen.
histboxpM
plots multiple histograms stacked vertically, for
variables in a data frame having a common group
variable (if any)
and combined using plotly::subplot
.
dhistboxp
is like histboxp
but no plotly
graphics
are actually drawn. Instead, a data frame suitable for use with
plotlyM
is returned. For dhistboxp
an additional level of
stratification strata
is implemented. group
causes a
different result here to produce backtoback histograms (in the case of
two groups) for each level of strata
.
histboxp(p = plotly::plot_ly(height=height), x, group = NULL,
xlab=NULL, gmd=TRUE, sd=FALSE, bins = 100, wmax=190, mult=7,
connect=TRUE, showlegend=TRUE)
dhistboxp(x, group = NULL, strata=NULL, xlab=NULL,
gmd=FALSE, sd=FALSE, bins = 100, nmin=5, ff1=1, ff2=1)
histboxpM(p=plotly::plot_ly(height=height, width=width), x, group=NULL,
gmd=TRUE, sd=FALSE, width=NULL, nrows=NULL, ncols=NULL, ...)
p 

x 
a numeric vector, or for 
group 
a discrete grouping variable. If omitted, defaults to a vector of ones 
strata 
a discrete numeric stratification variable. Values are also used to space out different spike histograms. Defaults to a vector of ones. 
xlab 
xaxis label, defaults to labelled version include units of measurement if any 
gmd 
set to 
sd 
set to 
width 
width in pixels 
nrows 
number of rows for layout of multiple plots 
ncols 
number of columns for layout of multiple plots. At most
one of 
bins 
number of equalwidth bins to use for spike histogram. If
the number of distinct values of 
nmin 
minimum number of nonmissing observations for a groupstratum combination before the spike histogram and quantiles are drawn 
ff1 , ff2 
fudge factors for position and bar length for spike histograms 
wmax , mult 
tweaks for margin to allocate 
connect 
set to 
showlegend 
used if producing multiple plots to be combined with

... 
other arguments for 
a plotly
object. For dhistboxp
a data frame as
expected by plotlyM
Frank Harrell
histSpike
, plot.describe
,
scat1d
## Not run:
dist < c(rep(1, 500), rep(2, 250), rep(3, 600))
Distribution < factor(dist, 1 : 3, c('Unimodal', 'Bimodal', 'Trimodal'))
x < c(rnorm(500, 6, 1),
rnorm(200, 3, .7), rnorm(50, 7, .4),
rnorm(200, 2, .7), rnorm(300, 5.5, .4), rnorm(100, 8, .4))
histboxp(x=x, group=Distribution, sd=TRUE)
X < data.frame(x, x2=runif(length(x)))
histboxpM(x=X, group=Distribution, ncols=2) # separate plots
## End(Not run)
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