Draw a X Y scatter plot with associated X and Y histograms with estimated densities. Will also draw density plots by groups, as well as distribution ellipses by group. Partly a demonstration of the use of layout. Also includes lowess smooth or linear model slope, as well as correlation.
scatterHist(x,y=NULL,smooth=TRUE,ab=FALSE, correl=TRUE,data=NULL, density=TRUE,means=TRUE,
ellipse=TRUE,digits=2,method="pearson",cex.cor=1,cex.point=1,
title="Scatter plot + density",
xlab=NULL,ylab=NULL,smoother=FALSE,nrpoints=0,xlab.hist=NULL,ylab.hist=NULL,grid=FALSE,
xlim=NULL,ylim=NULL,x.breaks=11,y.breaks=11,
x.space=0,y.space=0,freq=TRUE,x.axes=TRUE,y.axes=TRUE,size=c(1,2),
col=c("blue","red","black"),legend=NULL,alpha=.5,pch=21, show.d=TRUE,
x.arrow=NULL,y.arrow=NULL,d.arrow=FALSE,cex.arrow=1,...)
scatter.hist(x,y=NULL,smooth=TRUE,ab=FALSE, correl=TRUE,data=NULL,density=TRUE,
means=TRUE, ellipse=TRUE,digits=2,method="pearson",cex.cor=1,cex.point=1,
title="Scatter plot + density",
xlab=NULL,ylab=NULL,smoother=FALSE,nrpoints=0,xlab.hist=NULL,ylab.hist=NULL,grid=FALSE,
xlim=NULL,ylim=NULL,x.breaks=11,y.breaks=11,
x.space=0,y.space=0,freq=TRUE,x.axes=TRUE,y.axes=TRUE,size=c(1,2),
col=c("blue","red","black"),legend=NULL,alpha=.5,pch=21, show.d=TRUE,
x.arrow=NULL,y.arrow=NULL,d.arrow=FALSE,cex.arrow=1,...)The X vector, or the first column of a data.frame or matrix. Can be specified using formula input.
The Y vector, of if X is a data.frame or matrix, the second column of X
if TRUE, then add a loess smooth to the plot
if TRUE, then show the best fitting linear fit
TRUE: Show the correlation
if using formula input, the data must be specified
TRUE: Show the estimated densities
TRUE
TRUE: draw 1 and 2 sigma ellipses and smooth
How many digits to use if showing the correlation
Which method to use for correlation ("pearson","spearman","kendall") defaults to "pearson"
if TRUE, use smoothScatter instead of plot. Nice for large N.
If using smoothScatter, show nrpoints as dots. Defaults to 0
If TRUE, show a grid for the scatter plot.
Adjustment for the size of the correlation
Adjustment for the size of the data points
Label for the x axis
Label for the y axis
Allow specification for limits of x axis, although this seems to just work for the scatter plots.
Allow specification for limits of y axis
Number of breaks to suggest to the x axis histogram.
Number of breaks to suggest to the y axis histogram.
space between bars
Space between y bars
Show frequency counts, otherwise show density counts
Show the x axis for the x histogram
Show the y axis for the y histogram
The sizes of the ellipses (in sd units). Defaults to 1,2
Colors to use when showing groups
Amount of transparency in the density plots
Where to put a legend c("topleft","topright","top","left","right")
Base plot character (each group is one more)
Not currently available
Label for y axis histogram. Not currently available.
An optional title
If TRUE, show the distances between the groups
If TRUE, draw an arrow between the two centroids
optional lable for the arrow connecting the two groups for the x axis
optional lable for the arrow connecting the two groups for the y axis
cex control for the label size of the arrows.
Other parameters for graphics
Just a straightforward application of layout and barplot, with some tricks taken from pairs.panels. The various options allow for correlation ellipses (1 and 2 sigma from the mean), lowess smooths, linear fits, density curves on the histograms, and the value of the correlation. ellipse = TRUE implies smooth = TRUE. The grid option provides a background grid to the scatterplot.
If using grouping variables, will draw ellipses (defaults to 1 sd) around each centroid. This is useful when demonstrating Mahalanobis distances.
Formula input allows specification of grouping variables as well. )
For plotting data for two groups, Mahalobnis differences between the groups may be shown by drawing an arrow between the two centroids. This is a bit messy and it is useful to use pch="." in this case.
pairs.panels for multiple plots, multi.hist for multiple histograms. Perhaps the best example is found in the psychTools::GERAS data set.
# NOT RUN {
data(sat.act)
with(sat.act,scatterHist(SATV,SATQ))
scatterHist(SATV ~ SATQ,data=sat.act) #formula input
#or for something a bit more splashy
scatter.hist(sat.act[5:6],pch=(19+sat.act$gender),col=c("blue","red")[sat.act$gender],grid=TRUE)
#better yet
scatterHist(SATV ~ SATQ + gender,data=sat.act) #formula input with a grouping variable
# }
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