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.

`scatterplotMatrix(x, ...)`# S3 method for formula
scatterplotMatrix(formula, data=NULL, subset, labels, ...)

# S3 method for 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], id.location="lr",
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, legend.pos=NULL, row1attop=TRUE, ...)

spm(x, ...)

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,id.location

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.

var.labels

variable labels (for the diagonal of the plot).

diagonal

contents of the diagonal panels of the plot. If plotting by groups, a different
univariate display (with the exception of `"histogram"`

) will be drawn for each group.

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 other smoothers,
see `ScatterplotSmoothers`

.
Setting this argument to something other than a function, e.g., `FALSE`

suppresses the smoother.

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 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`

.

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, one for each variable, these are applied prior to plotting. If there are `groups`

and `by.groups`

is `TRUE`

, then the transformations are estimated *conditional* on the
`groups`

factor.

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 are
no groups, and successive colors for the groups if there are groups.

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.

legend.pos

position for the legend, specified as one of the keywords accepted by
`legend`

. If `NULL`

, the default, the position will vary by the
`diagonal`

argument --- e.g., `"topright"`

for `diagonal="density"`

.

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.

`NULL`

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

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

`pairs`

, `scatterplot`

,
`dataEllipse`

, `powerTransform`

,
`bcPower`

, `yjPower`

, `cov.trob`

,
`showLabels`

, `ScatterplotSmoothers`

.

# NOT RUN { 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) # }

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