- x
 
a vector of numeric data, or a data frame (for jitter2 or
       ecdfpM)
  
- object
 
a data frame or list (even with unequal number of observations per
    variable, as long as group is notspecified)
  
- side
 
axis side to use (1=bottom (default for histSpike), 2=left,
    3=top (default for scat1d), 4=right)
  
- frac
 
fraction of smaller of vertical and horizontal axes for tick mark
    lengths. Can be negative to move tick marks outside of plot. For
    histSpike, this is the relative y-direction length to be used for the
    largest frequency. When scat1d calls histSpike, it
    multiplies its frac argument by 2.5.  For histSpikeg,
    frac is a function of f, the vector of all frequencies.  The
		default function scales tick marks so that they are between 0.01 and
    0.03 of the y range, linearly scaled in the square root of the
    frequency less one.
  
- jitfrac
 
fraction of axis for jittering.  If
    \(\code{jitfrac} \le 0\), no
    jittering is done. If preserve=TRUE, the amount of
    jittering is independent of jitfrac.
  
- tfrac
 
Fraction of tick mark to actually draw.  If \(\code{tfrac}<1\),
    will draw a random fraction tfrac  of the line segment at
    each point. This is useful for very large samples or ones with some
    very dense points. The default value is 1 if the number of
    non-missing observations n  is less than 125, and
    \(\max{(.1, 125/n)}\) otherwise.
  
- eps
 
fraction of axis for determining overlapping points in x. For
    preserve=TRUE the default is 0 and original unique values are
    retained, bigger values of eps tends to bias observations from dense
    to sparse regions, but ranks are still preserved.
  
- lwd
 
line width for tick marks, passed to segments
  
- col
 
color for tick marks, passed to segments
  
- y
 
specify a vector the same length as x to draw tick marks
    along a curve instead of by one of the axes.  The y values
    are often predicted values from a model.  The side argument
    is ignored when y is given.  If the curve is already
    represented as a table look-up, you may specify it using the
    curve argument instead.  y may be a scalar to use a
    constant verticalplacement.
  
- curve
 
a list containing elements x and y for which linear
    interpolation is used to derive y values corresponding to
    values of x.  This results in tick marks being drawn along
    the curve.  For histSpike, interpolated y values are
    derived for binmidpoints.
	
- minimal
 
for histSpike set minimal=TRUE to draw a
       minimalist spike histogram with no y-axis.  This works best when
       produce graphics images that are short, e.g., have a height of
       two inches.  add is forced to be FALSE in this case
       so that a standalone graph is produced.  Only base graphics are
       used.
  
- bottom.align
 
set to TRUE to have the bottoms of tick marks (for
    side=1 or side=3) aligned at the y-coordinate.  The
    default behavior is to center the tick marks.  For
    datadensity.data.frame, bottom.align defaults to
    TRUE if nint>1.  In other words, if you are only
    labeling the first and last axis tick mark, the scat1d tick
    marks are centered on the variable's axis.
  
- preserve
 
set to TRUE to invoke jitter2
  
- fill
 
maximum fraction of the axis filled by jittered values. If d
    are duplicated values between a lower value l and upper value
    u, then d will be spread within
    \(\pm \code{fill}*\min{(u-d,d-l)}/2\).
  
- limit
 
specifies a limit for maximum shift in jittered values. Duplicate
    values will be spread within
    \(\pm\code{fill}*\min{(u-d,d-l)}/2\). The
    default TRUE restricts jittering to the smallest
    \(\min{(u-d,d-l)}/2\) observed and results
    in equal amount of jittering for all d. Setting to
    FALSE allows for locally different amount of jittering, using
    maximum space available.
  
- nhistSpike
 
If the number of observations exceeds or equals nhistSpike,
    scat1d will automatically call histSpike to draw the
    data density, to prevent the graphics file from being too large.
  
- type
 
used by or passed to histSpike.  Set to "count" to
    display frequency counts rather than relative frequencies, or
    "density" to display a kernel density estimate computed using
    the density function.
  
- grid
 
set to TRUE if the R grid package is in effect for
    the current plot
  
- nint
 
number of intervals to divide each continuous variable's axis for
    datadensity. For histSpike, is the number of
    equal-width intervals for which to bin x, and if instead
    nint is a character string (e.g.,nint="all"), the
    frequency tabulation is done with no binning.  In other words,
    frequencies for all unique values of x are derived and
    plotted.  For histSpikeg, if x has no more than
    nint unique values, all observed values are used, otherwise
    the data are rounded before tabulation so that there are no more
    than nint intervals.  For histSpike, nint is
       ignored if bins is given.
  
- bins
 
for histSpike specifies the actual cutpoints to use
       for binning x.  The default is to use nint in
       conjunction with xlim.
  
- ...
 
optional arguments passed to scat1d from datadensity
    or to histSpike from scat1d.  For histSpikep
           are passed to the lines list to add_trace.  For
					 ecdfpM these arguments are passed to add_lines.
  
- presorted
 
set to TRUE to prevent from sorting for determining the order
    \(l<d<u\). This is usefull if an existing
    meaningfull local order would be destroyed by sorting, as in
    \(\sin{(\pi*\code{sort}(\code{round}(\code{runif}(1000,0,10),1)))}\).
  
- group
 
an optional stratification variable, which is converted to a
    factor vector if it is not one already
  
- which
 
set which="continuous" to only plot continuous variables, or
    which="categorical" to only plot categorical, character, or
    discrete numeric ones.  By default, all types of variables are
    depicted.
  
- method.cat
 
set method.cat="freq" to depict frequencies of categorical
    variables with digits representing the cell frequencies, with size
    proportional to the square root of the frequency.  By default,
    vertical bars are used.
  
- col.group
 
colors representing the group strata.  The vector of colors
    is recycled to be the same length as the levels of group.
  
- n.unique
 
number of unique values a numeric variable must have before it is
    considered to be a continuous variable
  
- show.na
 
set to FALSE to suppress drawing the number of NAs to
    the right of each axis
  
- naxes
 
number of axes to draw on each page before starting a new plot.  You
    can set naxes larger than the number of variables in the data
    frame if you want to compress the plot vertically.
  
- q
 
a vector of quantiles to display.  By default, quantiles are not
    shown.
	
- extra
 
a two-vector specifying the fraction of the x
       range to add on the left and the fraction to add on the right
  
- cex.axis
 
character size for draw labels for axis tick marks
  
- cex.var
 
character size for variable names and frequence of NAs
  
- lmgp
 
spacing between numeric axis labels and axis (see par for
    mgp)
  
- tck
 
see tck under par
  
- ranges
 
a list containing ranges for some or all of the numeric variables.
    If ranges is not given or if a certain variable is not found
    in the list, the empirical range, modified by pretty, is
    used.  Example:
    ranges=list(age=c(10,100), pressure=c(50,150)).
  
- labels
 
a vector of labels to use in labeling the axes for
    datadensity.data.frame.  Default is to use the names of the
    variable in the input data frame.  Note: margin widths computed for
    setting aside names of variables use the names, and not these
    labels.
  
- minf
 
For histSpike, if minf is specified low bin
    frequencies are set to a minimum value of minf times the
    maximum bin frequency, so that rare data points will remain visible.
    A good choice of minf is 0.075.
    datadensity.data.frame passes minf=0.075 to
    scat1d to pass to histSpike.  Note that specifying
    minf will cause the shape of the histogram to be distorted
    somewhat.
  
- mult.width
 
multiplier for the smoothing window width computed by
    histSpike when type="density"
  
- xlim
 
a 2-vector specifying the outer limits of x for binning (and
    plotting, if add=FALSE and nint is a number).  For
    histSpikeg, observations outside the xlim range are ignored.
  
- ylim
 
y-axis range for plotting (if add=FALSE).  Often needed for
    histSpikeg to help scale the tick mark line segments.
  
- xlab
 
x-axis label (add=FALSE or for ecdfpM); default is
       name of input argument, or for ecdfpM comes from
       label and units attributes of the analysis
       variable.  For ecdfpM xlab may be a vector if there
       is more than one analysis variable.
  
- ylab
 
y-axis label (add=FALSE or for ecdfpM)
  
- add
 
set to TRUE to add the spike-histogram to an existing plot,
    to show marginal data densities
	
- formula
 
a formula of the form y ~ x1 or y ~ x1 + ... where
    y is the name of the y-axis variable being plotted
    with ggplot, x1 is the name of the x-axis
    variable, and optional ... are variables used by
    ggplot to produce multiple curves on a panel and/or facets.
	
- predictions
 
the data frame being plotted by ggplot, containing x
    and y coordinates of curves.  If omitted, spike histograms
    are drawn at the bottom (default) or top of the plot according to
    side.
	
- data
 
for histSpikeg is a mandatory data frame containing raw data whose
    frequency distribution is to be summarized, using variables in
    formula.
	
- plotly
 
an existing plotly object.  If not NULL,
           histSpikeg uses plotly instead of ggplot.
	
- lowess
 
set to TRUE to have histSpikeg add a geom_line
           layer to the ggplot2 graphic, containing
           lowess() nonparametric smoothers.  This causes the
           returned value of histSpikeg to be a list with two
           components: "hist" and "lowess" each containing
           a layer.  Fortunately, ggplot2 plots both layers
           automatically.  If the dependent variable is binary,
           iter=0 is passed to lowess so that outlier
           detection is turned off; otherwise iter=3 is passed.
- span
 
passed to lowess as the f argument
- histcol
 
color of line segments (tick marks) for
 histSpikeg.  Default is black.  Set to any color or to
   "default" to use the prevailing colors for the
   graphic.
- showlegend
 
set to FALSE too have the added plotly
  traces not have entries in the plot legend
- what
 
set to "1-F" to plot 1 minus the ECDF instead of the
       ECDF, "f" to plot cumulative frequency, or "1-f" to
       plot the inverse cumulative frequency
- height,width
 
passed to plot_ly
- colors
 
a vector of colors to pas to add_lines
- nrows,ncols
 
passed to plotly::subplot