`overplot`

graphs a set of variables defined on the same x-range
but which have varying y-ranges on the same plotting area. For each
set of y-values it uses a different color and line-type and and draws
a correspondingly colored and line-typed axis. `panel.overplot`

is used by `overplot`

to draw the individual graphs.

```
overplot(formula, data = parent.frame(), same.scale = FALSE, xlab, ylab,
xlim, ylim, min.y, max.y, log = "", panel = "panel.overplot",
subset, plot = TRUE, groups, main, f = 2/3, ...)
```

formula

Formula describing the x and y variables. It should be of the form x ~ y|z. The conditioning variable (z) should be a factor.

same.scale

Logical value indicating whether the plot region
should have the same range for all plots. Defaults to `FALSE`

.

xlab, ylab, xlim, ylim, main

Standard plotting parameters. See
`plot`

for details

min.y, max.y

Scalar or vector values used to specify the y plotting limits for individual plots. If a single scalar value is provided, it will be used for all plots. These parameters can be used specify one end of the individual plot ranges, while allowing the other end to vary with the data. EG, to force 0 to always be within the plot region.

log

character string '', 'x', 'y', or 'xy', indicating which axes should be plotted on a log scale. Defaults to '' (neither).

panel

a plotting function to be called to draw the individual
plots. Defaults to `overplot.panel`

, which plots the points
and a `lowess`

smooth.

plot

Logical value indicating whether to draw the plot.

groups

(optional) character vector giving the names of levels of the conditioning variable to plot. Defaults to all levels of the conditioning variable.

f

Smoothing parameter for `lowess`

data, subset, …

parameters passed to `model.frame`

to
obtain the data to be plotted from the formula.

A copy of the data split by the conditioning variable.

This function essentially performs

tmp <- split(data, z)

for(i in levels(z))

plot( x ~ y, data=tmp[[z]] )

except that all of the plots are shown on the same plotting region and varying scales for each value of z are handled nicely.

`interaction.plot`

,
`coplot`

for alternative visualizations of 3-way data.

# NOT RUN { # Example teratogenicity rtPCR data data(rtPCR) # same scale overplot( RQ ~ Conc..ug.ml. | Test.Substance, data=rtPCR, subset=Detector=="ProbeType 1" & Conc..ug.ml. > 0, same.scale=TRUE, log="xy", f=3/4, main="Detector=ProbeType 1", xlab="Concentration (ug/ml)", ylab="Relative Gene Quantification" ) # different scales, but force lower limit to 0.01 overplot( RQ ~ Conc..ug.ml. | Test.Substance, data=rtPCR, subset=Detector=="ProbeType 8" & Conc..ug.ml. > 0, log="xy", f=3/4, main="Detector=ProbeType 8", xlab="Concentration (ug/ml)", ylab="Relative Gene Quantification", min.y=0.01 ) # }