gglagplot: Time series lag ggplots

In forecast: Forecasting Functions for Time Series and Linear Models

Time series lag ggplots

Description

Plots a lag plot using ggplot.

Usage

gglagplot(
  x,
  lags = if (frequency(x) > 9) 16 else 9,
  set.lags = 1:lags,
  diag = TRUE,
  diag.col = "gray",
  do.lines = TRUE,
  colour = TRUE,
  continuous = frequency(x) > 12,
  labels = FALSE,
  seasonal = TRUE,
  ...
)

gglagchull(
  x,
  lags = if (frequency(x) > 1) min(12, frequency(x)) else 4,
  set.lags = 1:lags,
  diag = TRUE,
  diag.col = "gray",
  ...
)

Arguments

x	a time series object (type ts).
lags	number of lag plots desired, see arg set.lags.
set.lags	vector of positive integers specifying which lags to use.
diag	logical indicating if the x=y diagonal should be drawn.
diag.col	color to be used for the diagonal if(diag).
do.lines	if TRUE, lines will be drawn, otherwise points will be drawn.
colour	logical indicating if lines should be coloured.
continuous	Should the colour scheme for years be continuous or discrete?
labels	logical indicating if labels should be used.
seasonal	Should the line colour be based on seasonal characteristics (TRUE), or sequential (FALSE).
...	Not used (for consistency with lag.plot)

Details

"gglagplot" will plot time series against lagged versions of themselves. Helps visualising 'auto-dependence' even when auto-correlations vanish.

"gglagchull" will layer convex hulls of the lags, layered on a single plot. This helps visualise the change in 'auto-dependence' as lags increase.

Value

None.

Author(s)

Mitchell O'Hara-Wild

See Also

stats::lag.plot()

Examples

gglagplot(woolyrnq)
gglagplot(woolyrnq, seasonal = FALSE)

lungDeaths <- cbind(mdeaths, fdeaths)
gglagplot(lungDeaths, lags = 2)
gglagchull(lungDeaths, lags = 6)

gglagchull(woolyrnq)

forecast documentation built on March 18, 2026, 9:07 a.m.