scatterplotMatrix

0th

Percentile

Scatterplot Matrices

Enhanced scatterplot matrices with univariate displays down the diagonal; spm is an abbreviation for scatterplotMatrix. This function just sets up a call to pairs with custom panel functions.

Keywords
hplot
Usage
scatterplotMatrix(x, ...)

## S3 method for class 'formula':
scatterplotMatrix(formula, data=NULL, subset, labels, ...)

## S3 method for class 'default':
scatterplotMatrix(x, var.labels=colnames(x), 
    diagonal=c("density", "boxplot", "histogram", "oned", "qqplot", "none"), 
    adjust=1, nclass,
    plot.points=TRUE, smoother=loessLine, smoother.args=list(), smooth, span,
    spread = !by.groups, reg.line=lm,
    transform=FALSE, family=c("bcPower", "yjPower"),
    ellipse=FALSE, levels=c(.5, .95), robust=TRUE,
    groups=NULL, by.groups=FALSE, 
    use=c("complete.obs", "pairwise.complete.obs"),
    labels, id.method="mahal", id.n=0, id.cex=1, id.col=palette()[1],
    col=if (n.groups == 1) palette()[3:1] else rep(palette(), length=n.groups),
    pch=1:n.groups, lwd=1, lty=1, 
    cex=par("cex"), cex.axis=par("cex.axis"), cex.labels=NULL, 
    cex.main=par("cex.main"), 
    legend.plot=length(levels(groups)) > 1, row1attop=TRUE, ...)

spm(x, ...)
Arguments
x
a data matrix, numeric data frame.
formula
a one-sided model formula, of the form ~ x1 + x2 + ... + xk or ~ x1 + x2 + ... + xk | z where z evaluates to a factor or other variable to divide the data into groups.
data
for scatterplotMatrix.formula, a data frame within which to evaluate the formula.
subset
expression defining a subset of observations.
labels,id.method,id.n,id.cex,id.col
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 gr
var.labels
variable labels (for the diagonal of the plot).
diagonal
contents of the diagonal panels of the plot.
adjust
relative bandwidth for density estimate, passed to density function.
nclass
number of bins for histogram, passed to hist function.
plot.points
if TRUE the points are plotted in each off-diagonal panel.
smoother
a function to draw a nonparametric-regression smooth; the default is gamLine, which uses the gam function in the mgcv package. For this and o
smoother.args
a list of named values to be passed to the smoother function; the specified elements of the list depend upon the smoother (see ScatterplotSmoothers).
smooth, span
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.
spread
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
reg.line
if not FALSE a line is plotted using the function given by this argument; e.g., using rlm in package MASS plots a robust-regression line.
transform
if TRUE, multivariate normalizing power transformations are computed with powerTransform, rounding the estimated powers to `nice' values for plotting; if a vector of powers, o
family
family of transformations to estimate: "bcPower" for the Box-Cox family or "yjPower" for the Yeo-Johnson family (see powerTransform).
ellipse
if TRUE data-concentration ellipses are plotted in the off-diagonal panels.
levels
levels or levels at which concentration ellipses are plotted; the default is c(.5, .9).
robust
if TRUE use the cov.trob function in the MASS package to calculate the center and covariance matrix for the data ellipses.
groups
a factor or other variable dividing the data into groups; groups are plotted with different colors and plotting characters.
by.groups
if TRUE, regression lines are fit by groups.
use
if "complete.obs" (the default), cases with missing data are omitted; if "pairwise.complete.obs"), all valid cases are used in each panel of the plot.
pch
plotting characters for points; default is the plotting characters in order (see par).
col
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
lwd
width of linear-regression lines (default 1).
lty
type of linear-regression lines (default 1, solid line).
cex, cex.axis, cex.labels, cex.main
set sizes of various graphical elements (see par).
legend.plot
if TRUE then a legend for the groups is plotted in the first diagonal cell.
row1attop
If TRUE (the default) the first row is at the top, as in a matrix, as opposed to at the bottom, as in graph (argument suggested by Richard Heiberger).
...
arguments to pass down.
Value

  • NULL. This function is used for its side effect: producing a plot.

References

Fox, J. and Weisberg, S. (2011) An R Companion to Applied Regression, Second Edition, Sage.

See Also

pairs, scatterplot, dataEllipse, powerTransform, bcPower, yjPower, cov.trob, showLabels, ScatterplotSmoothers.

Aliases
  • scatterplotMatrix
  • scatterplotMatrix.formula
  • scatterplotMatrix.default
  • spm
Examples
scatterplotMatrix(~ income + education + prestige | type, data=Duncan)
scatterplotMatrix(~ income + education + prestige, 
    transform=TRUE, data=Duncan, smoother=loessLine)
scatterplotMatrix(~ income + education + prestige | type, smoother=FALSE, 
	by.group=TRUE, transform=TRUE, data=Duncan)
Documentation reproduced from package car, version 2.0-20, License: GPL (>= 2)

Community examples

mkjiskrz@gmail.com at Jun 30, 2017 car v2.1-4

## There is no definition of the plot that is produced - e.g. what are exactly the green and red lines. This should be written as the most important thing in the documentation. Documentation should focus on telling what the function exactly does - it is completely missing. library(car) print('There is no definition of the plot that is produced - e.g. what are exactly the green and red lines. This should be written as the most important thing in the documentation. Documentation should focus on telling what the function exactly does - it is completely missing.') scatterplotMatrix(~ income + education)