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)
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.
Examples
gglagplot(woolyrnq)
gglagplot(woolyrnq,seasonal=FALSE)
lungDeaths <- cbind(mdeaths, fdeaths)
gglagplot(lungDeaths, lags=2)
gglagchull(lungDeaths, lags=6)
gglagchull(woolyrnq)
