R: Conditioning Plots

coplot {base}

R Documentation

Conditioning Plots

Description

This function produces two variants of the conditioning plots discussed in the reference below.

Usage

coplot(formula, data, given.values, panel = points, rows, columns,
       show.given = TRUE, col = par("fg"), pch = par("pch"), 
       bar.bg = c(num = gray(0.8), fac = gray(0.95)),
       xlab = c(x.name, paste("Given :", a.name)),
       ylab = c(y.name, paste("Given :", b.name)),
       subscripts = FALSE,
       axlabels = function(f) abbreviate(levels(f)),
       number = 6, overlap = 0.5, xlim, ylim, ...) 
co.intervals(x, number = 6, overlap = 0.5)

Arguments

`formula`	a formula describing the form of conditioning plot. A formula of the form `y ~ x \| a` indicates that plots of `y` versus `x` should be produced conditional on the variable `a`. A formula of the form `y ~ x\| a * b` indicates that plots of `y` versus `x` should be produced conditional on the two variables `a` and `b`. All three or four variables may be either numeric or factors. When `x` or `y` are factors, the result is almost as if `as.numeric()` was applied, whereas for factor `a` or `b`, the conditioning (and its graphics if `show.given` is true) are adapted.
`data`	a data frame containing values for any variables in the formula. By default the environment where `coplot` was called from is used.
`given.values`	a value or list of two values which determine how the conditioning on `a` and `b` is to take place. When there is no `b` (i.e., conditioning only on `a`), usually this is a matrix with two columns each row of which gives an interval, to be conditioned on, but is can also be a single vector of numbers or a set of factor levels (if the variable being conditioned on is a factor). In this case (no `b`), the result of `co.intervals` can be used directly as `given.values` argument.
`panel`	a `function(x, y, col, pch, ...)` which gives the action to be carried out in each panel of the display. The default is `points`.
`rows`	the panels of the plot are laid out in a `rows` by `columns` array. `rows` gives the number of rows in the array.
`columns`	the number of columns in the panel layout array.
`show.given`	logical (possibly of length 2 for 2 conditioning variables): should conditioning plots be shown for the corresponding conditioning variables (default `TRUE`)

`col`	a vector of colors to be used to plot the points. If too short, the values are recycled.
`pch`	a vector of plotting symbols or characters. If too short, the values are recycled.
`bar.bg`	a named vector with components `"num"` and `"fac"` giving the background colors for the (shingle) bars, for numeric and factor conditioning variables respectively.
`xlab`	character; labels to use for the x axis and the first conditioning variable. If only one label is given, it is used for the x axis and the default label is used for the conditioning variable.
`ylab`	character; labels to use for the y axis and any second conditioning variable.
`subscripts`	logical: if true the panel function is given an additional (third) argument `subscripts` giving the subscripts of the data passed to that panel.
`axlabels`	function for creating axis (tick) labels when x or y are factors.
`number`	integer; the number of conditioning intervals, for a and b, possibly of length 2. It is only used if the corresponding conditioning variable is not a `factor`.
`overlap`	numeric < 1; the fraction of overlap of the conditioning variables, possibly of length 2 for x and y direction. When overlap < 0, there will be gaps between the data slices.
`xlim`	the range for the x axis.
`ylim`	the range for the y axis.
`...`	additional arguments to the panel function.
`x`	a numeric vector.

Details

In the case of a single conditioning variable a, when both rows and columns are unspecified, a “close to square” layout is chosen with columns >= rows.

In the case of multiple rows, the order of the panel plots is from the bottom and from the left (corresponding to increasing a, typically).

Value

co.intervals(., number, .) returns a (number \times 2) matrix, say ci, where ci[k,] is the range of x values for the k-th interval.

References

Cleveland, W. S. (1993) Visualizing Data. New Jersey: Summit Press.

Examples

## Tonga Trench Earthquakes
data(quakes)
coplot(lat ~ long | depth, data = quakes)
given.depth <- co.intervals(quakes$depth, number=4, overlap=.1)
coplot(lat ~ long | depth, data = quakes, given.v=given.depth, rows=1)

## Conditioning on 2 variables:
ll.dm <- lat ~ long | depth * mag
coplot(ll.dm, data = quakes)
coplot(ll.dm, data = quakes, number=c(4,7), show.given=c(TRUE,FALSE))
coplot(ll.dm, data = quakes, number=c(3,7),
       overlap=c(-.5,.1)) # negative overlap DROPS values

data(warpbreaks)
## given two factors
coplot(breaks ~ 1:54 | wool * tension, data = warpbreaks, show.given = 0:1)
coplot(breaks ~ 1:54 | wool * tension, data = warpbreaks,
       col = "red", bg = "pink", pch = 21,
       bar.bg = c(fac = "light blue"))

## Example with empty panels:
data(state)
attach(data.frame(state.x77))#> don't need `data' arg. below
coplot(Life.Exp ~ Income | Illiteracy * state.region, number = 3,
       panel = function(x, y, ...) panel.smooth(x, y, span = .8, ...))
## y ~ factor -- not really sensical, but `show off':
coplot(Life.Exp ~ state.region | Income * state.division,
       panel = panel.smooth)
detach() # data.frame(state.x77)

[Package base version 1.5.0 ]