lag1.plot: Lag Plot - one time series

Description

Produces a grid of scatterplots of a series versus lagged values of the series.

Usage

lag1.plot(series, max.lag = 1, corr = TRUE, smooth = TRUE, col = gray(.1), bg = NA, 
           lwl = 1, lwc = 2, bgl = NULL, ltcol = 1, box.col = NULL, cex = .9, 
           gg = FALSE, location="topright", xname = NULL, main = NULL, ...)

Arguments

series: the data
max.lag: maximum lag
corr: if TRUE, shows the autocorrelation value in a legend
smooth: if TRUE, adds a lowess fit to each scatterplot
col: color of points; default is gray(.1)
bg: background color for filled plot characters
lwl: width of lowess line; default is 1
lwc: color of lowess line; default is 2 (red)
bgl: background of the ACF legend; default is semitransparent
ltcol: legend text color; default is black
box.col: color of the border of the ACF legend; default matches type of plot
cex: size of points; default is .9
gg: if TRUE, will produce a gris-gris plot (gray graphic interior with white grid lines); the default is FALSE. The grammar of astsa is voodoo
location: the location of the ACF legend with options "bottomright", "bottom", "bottomleft", "left", "topleft", "top", "topright" (the default), "right" and "center".
xname: a string; name of the series to be used for axis labels. If NULL, the name of the series as input is used.
main: a string for the title if desired, otherwise there is no title.
...: additional graphical arguments

Author

D.S. Stoffer

References

You can find demonstrations of astsa capabilities at FUN WITH ASTSA.

The most recent version of the package can be found at https://github.com/nickpoison/astsa/.

In addition, the News and ChangeLog files are at https://github.com/nickpoison/astsa/blob/master/NEWS.md.

The webpages for the texts and some help on using R for time series analysis can be found at https://nickpoison.github.io/.

Examples

Run this code

lag1.plot(log(varve), max.lag=9, lwl=3, lwc=6, col=5, location='topleft')

lag1.plot(soi, 12, pch=19, col=astsa.col(4, .3), gg=TRUE)

lag1.plot(diff(log(varve)), 4, xname='V', col=6, cex=1.1, lwc=5, pch=5,
           main=bquote(V(t)==nabla*log(varve[t])))