Time series plotting methods

This function handles time series plotting, including cut-and-stack plots. Examples are given of superposing, juxtaposing and styling different time series.

Usage

# S3 method for class 'ts'
xyplot(x, data = NULL,
       screens = if (superpose) 1 else colnames(x),
       ...,
       superpose = FALSE,
       cut = FALSE,
       type = "l",
       col = NULL,
       lty = NULL,
       lwd = NULL,
       pch = NULL,
       cex = NULL,
       fill = NULL,
       auto.key = superpose,
       panel = if (superpose) "panel.superpose"
               else "panel.superpose.plain",
       par.settings = list(),
       layout = NULL, as.table = TRUE,
       xlab = "Time", ylab = NULL,
       default.scales = list(y = list(relation =
           if (missing(cut)) "free" else "same")))

Arguments

x

an object of class ts, which may be multi-variate, i.e. have a matrix structure with multiple columns.

data

not used, and must be left as NULL.

...

additional arguments passed to xyplot, which may pass them on to panel.xyplot.

screens

factor (or coerced to factor) whose levels specify which panel each series is to be plotted in. screens = c(1, 2, 1) would plot series 1, 2 and 3 in panels 1, 2 and 1. May also be a named list, see Details below.

superpose

overlays all series in one panel (via screens = 1) and uses grouped style settings (from trellis.par.get("superpose.line"), etc). Note that this is just a convenience argument: its only action is to change the default values of other arguments.

cut

defines a cut-and-stack plot. cut can be a list of arguments to the function equal.count, i.e. number (number of intervals to divide into) and overlap (the fraction of overlap between cuts, default 0.5). If cut is numeric this is passed as the number argument.

cut = TRUE tries to choose an appropriate number of cuts (up to a maximum of 6), using banking, and assuming a square plot region. This should have the effect of minimising wasted space when aspect = "xy".

type, col, lty, lwd, pch, cex, fill

graphical arguments, which are processed and eventually passed to panel.xyplot. These arguments can also be vectors or (named) lists, see Details for more information.

auto.key

a logical, or a list describing how to draw a key. See the auto.key entry in xyplot. The default here is to draw lines, not points, and any specified style arguments should show up automatically.

panel

the panel function. It is recommended to leave this alone, but one can pass a panel.groups argument which is handled by panel.superpose for each series.

par.settings

style settings beyond the standard col, lty, lwd, etc; see trellis.par.set and simpleTheme.

layout

numeric vector of length 2 specifying number of columns and rows in the plot. The default is to fill columns with up to 6 rows.

as.table

to draw panels from top to bottom. The order is determined by the order of columns in x.

xlab, ylab

X axis and Y axis labels; see xyplot. Note in particular that ylab may be a character vector, in which case the labels are spaced out equally, to correspond to the panels; but NOTE in this case the vector should be reversed OR the argument as.table set to FALSE.

default.scales

scales specification. The default is set to have "free" Y axis scales unless cut is given. Note, users should pass the scales argument rather than default.scales.

Details

The handling of several graphical parameters is more flexible for multivariate series. These parameters can be vectors of the same length as the number of series plotted or are recycled if shorter. They can also be (partially) named list, e.g., list(A = c(1,2), c(3,4)) in which c(3, 4) is the default value and c(1, 2) the value only for series A. The screens argument can be specified in a similar way.

Some examples are given below.

Value

An object of class "trellis". The update method can be used to update components of the object and the print method (usually called by default) will plot it on an appropriate plotting device.

Author

Gabor Grothendieck, Achim Zeileis, Deepayan Sarkar and Felix Andrews felix@nfrac.org.

The first two authors developed xyplot.ts in their zoo package, including the screens approach. The third author developed a different xyplot.ts for cut-and-stack plots in the latticeExtra package. The final author fused these together.

References

Sarkar, Deepayan (2008) Lattice: Multivariate Data Visualization with R, Springer. http://lmdvr.r-forge.r-project.org/ (cut-and-stack plots)

Examples

xyplot(ts(c(1:10,10:1)))


### Figure 14.1 from Sarkar (2008)
xyplot(sunspot.year, aspect = "xy",
       strip = FALSE, strip.left = TRUE,
       cut = list(number = 4, overlap = 0.05))


### A multivariate example; first juxtaposed, then superposed
xyplot(EuStockMarkets, scales = list(y = "same"))

xyplot(EuStockMarkets, superpose = TRUE, aspect = "xy", lwd = 2,
    type = c("l","g"), ylim = c(0, max(EuStockMarkets)))


### Examples using screens (these two are identical)
xyplot(EuStockMarkets, screens = c(rep("Continental", 3), "UK"))

xyplot(EuStockMarkets, screens = list(FTSE = "UK", "Continental"))


### Automatic group styles
xyplot(EuStockMarkets, screens = list(FTSE = "UK", "Continental"),
    superpose = TRUE)


xyplot(EuStockMarkets, screens = list(FTSE = "UK", "Continental"),
    superpose = TRUE, xlim = extendrange(1996:1998),
    par.settings = standard.theme(color = FALSE))


### Specifying styles for series by name
xyplot(EuStockMarkets, screens = list(FTSE = "UK", "Continental"),
    col = list(DAX = "red", FTSE = "blue", "black"), auto.key = TRUE)


xyplot(EuStockMarkets, screens = list(FTSE = "UK", "Continental"),
    col = list(DAX = "red"), lty = list(SMI = 2), lwd = 1:2,
    auto.key = TRUE)


### Example with simpler data, few data points
set.seed(1)
z <- ts(cbind(a = 1:5, b = 11:15, c = 21:25) + rnorm(5))
xyplot(z, screens = 1)

xyplot(z, screens = list(a = "primary (a)", "other (b & c)"),
  type = list(a = c("p", "h"), b = c("p", "s"), "o"),
  pch = list(a = 2, c = 3), auto.key = list(type = "o"))