Makes enhanced scatterplots, with boxplots in the margins, a nonparametric regression smooth,
smoothed conditional spread, outlier identification, and a regression line;
sp is an abbreviation for scatterplot.
scatterplot(x, ...)# S3 method for formula
scatterplot(formula, data, subset, xlab, ylab, legend.title, legend.coords,
labels, ...)
# S3 method for default
scatterplot(x, y,
smoother=loessLine, smoother.args=list(), smooth, span,
spread=!by.groups, reg.line=lm,
boxplots=if (by.groups) "" else "xy",
xlab=deparse(substitute(x)), ylab=deparse(substitute(y)), las=par("las"),
lwd=1, lty=1,
labels, id.method = "mahal",
id.n = if(id.method[1]=="identify") length(x) else 0,
id.cex = 1, id.col = palette()[1], id.location="lr",
log="", jitter=list(), xlim=NULL, ylim=NULL,
cex=par("cex"), cex.axis=par("cex.axis"), cex.lab=par("cex.lab"),
cex.main=par("cex.main"), cex.sub=par("cex.sub"),
groups, by.groups=!missing(groups),
legend.title=deparse(substitute(groups)), legend.coords, legend.columns,
ellipse=FALSE, levels=c(.5, .95), robust=TRUE,
col=if (n.groups == 1) palette()[3:1] else rep(palette(), length=n.groups),
pch=1:n.groups,
legend.plot=!missing(groups), reset.par=TRUE, grid=TRUE, ...)
sp(x, ...)
vector of horizontal coordinates (or first argument of generic function).
vector of vertical coordinates.
a ``model'' formula, of the form y ~ x or
(to plot by groups) y ~ x | z, where z evaluates to a factor
or other variable dividing the data into groups. If x is a factor, then parallel boxplots
are produced using the Boxplot function.
data frame within which to evaluate the formula.
expression defining a subset of observations.
a function to draw a nonparametric-regression smooth; the default is loessLine,
which does loess smoothing. The function gamLine fits a generalized additive model and
allows including a link and error function.
See ScatterplotSmoothers.
Setting this argument to something other than a function, e.g., FALSE suppresses the smoother.
a list of named values to be passed to the smoother function; the specified elements of the
list depend upon the smoother (see ScatterplotSmoothers).
these arguments are included for backwards compatility:
if smooth=TRUE then smoother is set to loessLine,
and if span is specified, it is added to smoother.args.
if TRUE, estimate the (square root) of the variance function. For loessLine and
for gamLine, this is done by separately smoothing the squares of the postive and negative
residuals from the mean fit, and then adding the square root of the fitted values to the mean fit. For
quantregLine, fit the .25 and .75 quantiles with a quantile regression additive model.
The default is TRUE if by.groups=FALSE and FALSE is by.groups=TRUE.
function to draw a regression line on the plot
or FALSE not to plot a regression line.
if "x" a boxplot for x is drawn below the plot;
if "y" a boxplot for y is drawn to the left of the plot;
if "xy" both boxplots are drawn; set to "" or FALSE to
suppress both boxplots.
label for horizontal axis.
label for vertical axis.
if 0, ticks labels are drawn parallel to the
axis; set to 1 for horizontal labels (see par).
width of linear-regression lines (default 1).
type of linear-regression lines (default 1, solid line).
Arguments for the labelling of
points. The default is id.n=0 for labeling no points. See
showLabels for details of these arguments. If the plot uses
different colors for groups, then the id.col argument is ignored and
label colors are determined by the col argument.
a vector of point labels; if absent, the function tries to determine reasonable labels, and, failing that, will use observation numbers.
same as the log argument to plot, to produce log axes.
a list with elements x or y or both, specifying jitter factors
for the horizontal and vertical coordinates of the points in the scatterplot. The
jitter function is used to randomly perturb the points; specifying a
factor of 1 produces the default jitter. Fitted lines are unaffected by the jitter.
the x limits (min, max) of the plot; if NULL, determined from the data.
the y limits (min, max) of the plot; if NULL, determined from the data.
a factor or other variable dividing the data into groups; groups are plotted with different colors and plotting characters.
if TRUE, regression lines are fit by groups.
title for legend box; defaults to the name of the groups variable.
coordinates for placing legend; can be a list with components x and y to
specify the coordinates of the upper-left-hand corner of the legend; or a quoted keyword, such as "topleft",
recognized by legend.
number of columns for the legend; if absent will be supplied automatically to prefer horizontal legends when plotted above the graph.
if TRUE data-concentration ellipses are plotted.
level or levels at which concentration ellipses are plotted;
the default is c(.5, .95).
if TRUE (the default) use the cov.trob function in the MASS package
to calculate the center and covariance matrix for the data ellipses.
colors for lines and points; the default is taken from the color palette,
with palette()[3] for linear regression lines, palette()[2] for nonparametric regression lines, and palette()[1]
for points if there are
no groups, and successive colors for the groups if there are groups.
plotting characters for points; default is the plotting characters in
order (see par).
set sizes of various graphical elements;
(see par).
if TRUE then a legend for the groups is plotted in the upper margin.
if TRUE then plotting parameters are reset to their previous values
when scatterplot exits; if FALSE then the mar and mfcol parameters are
altered for the current plotting device. Set to FALSE if you want to add graphical elements
(such as lines) to the plot.
other arguments passed down and to plot.
If TRUE, the default, a light-gray background grid is put on the graph
If points are identified, their labels are returned; otherwise NULL is returned invisibly.
boxplot,
jitter, legend,
scatterplotMatrix, dataEllipse, Boxplot,
cov.trob,
showLabels, ScatterplotSmoothers.
scatterplot(prestige ~ income, data=Prestige, ellipse=TRUE)
if (interactive()){
scatterplot(prestige ~ income, data=Prestige, smoother=quantregLine)
}
scatterplot(prestige ~ income|type, data=Prestige, smoother=loessLine,
smoother.args=list(span=1))
scatterplot(prestige ~ income|type, data=Prestige, legend.coords="topleft")
scatterplot(vocabulary ~ education, jitter=list(x=1, y=1),
data=Vocab, id.n=0, smoother=FALSE)
scatterplot(infant.mortality ~ gdp, log="xy", data=UN, id.n=5)
scatterplot(income ~ type, data=Prestige)
scatterplot(infant.mortality ~ gdp, id.method="identify", data=UN)
scatterplot(infant.mortality ~ gdp, id.method="identify", smoother=loessLine, data=UN)
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