gglagplot | R Documentation |
Plots a lag plot using ggplot.
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",
...
)
x |
a time series object (type |
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) |
“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.
None.
Mitchell O'Hara-Wild
lag.plot
gglagplot(woolyrnq)
gglagplot(woolyrnq,seasonal=FALSE)
lungDeaths <- cbind(mdeaths, fdeaths)
gglagplot(lungDeaths, lags=2)
gglagchull(lungDeaths, lags=6)
gglagchull(woolyrnq)
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