Produces a plot of local multiple cross-regressions.
plot_local.multiple.cross.regression(Lst, lmax, nsig=2, xaxt="s")A list from local.multiple.cross.regression.
maximum lag (and lead).
An optional value for the number of significant variables to plot_ Default is 2.
An optional vector of labels for the "x" axis. Default is 1:n.
Plot.
The routine produces time series plots of local multiple cross-regressions with their confidence interval for every lag and lead. Also, at every upturn and downturn of the corresponding local multiple cross-correlation, the name of the variable that maximizes that multiple correlation against the rest is shown on top. The others are named ordered by significance when they are relevant.
Fern<U+00E1>ndez-Macho, J., 2018. Time-localized wavelet multiple regression and correlation, Physica A: Statistical Mechanics, vol. 490, p. 1226--1238. <DOI:10.1016/j.physa.2017.11.050>