forecast (version 8.5)

gglagplot: Time series lag ggplots

Description

Plots a lag plot using ggplot.

Usage

gglagplot(x, lags = ifelse(frequency(x) > 9, 16, 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 = ifelse(frequency(x) > 1, min(12, frequency(x)), 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)

Value

None.

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.

See Also

lag.plot

Examples

# NOT RUN {
gglagplot(woolyrnq)
gglagplot(woolyrnq,seasonal=FALSE)

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

gglagchull(woolyrnq)

# }