a vector of numeric data, or a data frame (for jitter2 or ecdfpM)

a data frame or list (even with unequal number of observations per variable, as long as group is notspecified)

axis side to use (1=bottom (default for histSpike), 2=left, 3=top (default for scat1d), 4=right)

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.

fraction of axis for jittering. If \code{jitfrac} <= 0, no jittering is done. If preserve=TRUE, the amount of jittering is independent of jitfrac.

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/\var{n})} otherwise.

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.

line width for tick marks, passed to segments

color for tick marks, passed to segments

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.

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.

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.

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.

set to TRUE to invoke jitter2

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 +/- \code{fill}*min(\var{u}-\var{d},\var{d}-\var{l})/2.

specifies a limit for maximum shift in jittered values. Duplicate values will be spread within +/- \code{fill}*min(\var{u}-\var{d},\var{d}-\var{l})/2. The default TRUE restricts jittering to the smallest \min{(\var{u}-\var{d},\var{d}-\var{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.

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.

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.

set to TRUE if the R grid package is in effect for the current plot

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.

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.

set to TRUE to prevent from sorting for determining the order \var{l}<\var{d}<\var{u}. This is usefull if an existing meaningfull local order would be destroyed by sorting, as in \sin{(π*\code{sort}(\code{round}(\code{runif}(1000,0,10),1)))}.

an optional stratification variable, which is converted to a factor vector if it is not one already

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.

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.

colors representing the group strata. The vector of colors is recycled to be the same length as the levels of group.

number of unique values a numeric variable must have before it is considered to be a continuous variable

set to FALSE to suppress drawing the number of NAs to the right of each axis

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.

a vector of quantiles to display. By default, quantiles are not shown.

a two-vector specifying the fraction of the x range to add on the left and the fraction to add on the right

character size for draw labels for axis tick marks

character size for variable names and frequence of NAs

spacing between numeric axis labels and axis (see par for mgp)

see tck under par

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)).

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.

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.

multiplier for the smoothing window width computed by histSpike when type="density"

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.

y-axis range for plotting (if add=FALSE). Often needed for histSpikeg to help scale the tick mark line segments.

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.

y-axis label (add=FALSE or for ecdfpM)

set to TRUE to add the spike-histogram to an existing plot, to show marginal data densities

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.

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.

for histSpikeg is a mandatory data frame containing raw data whose frequency distribution is to be summarized, using variables in formula.

an existing plotly object. If not NULL, histSpikeg uses plotly instead of ggplot.

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.

passed to lowess as the f argument

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.

set to FALSE too have the added plotly traces not have entries in the plot legend

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

passed to plot_ly

a vector of colors to pas to add_lines

passed to plotly::subplot