| plot_local.multiple.cross.correlation {wavemulcor} | R Documentation |
Auxiliary routine for plotting local multiple cross-correlations
Description
Produces a plot of local multiple cross-correlations.
Usage
plot_local.multiple.cross.correlation(Lst, lmax, xaxt="s")
Arguments
Lst |
A list from local.multiple.cross.regression or local.multiple.cross.correlation. |
lmax |
maximum lag (and lead). |
xaxt |
An optional vector of labels for the "x" axis. Default is 1:n. |
Details
The routine produces a set of time series plots of local multiple cross-correlations, one per lag and lead, each with its confidence interval. Also, at every upturn and downturn, the name of the variable that maximizes its multiple correlation against the rest is shown. Note that the routine is optimize for local.multiple.cross.regression. If you want to use output from local.multiple.cross.correlation function then you must create an empty list and put that output into a list element named cor like this: Lst <- list(); Lst$cor <- local.multiple.cross.correlation(xx, M, window=window, lag.max=lmax); Lst$YmaxR <- Lst2$cor$YmaxR; Lst$cor$YmaxR <- NULL.
Value
Plot.
Author(s)
Javier Fernández-Macho, Dpt. of Quantitative Methods, University of the Basque Country, Agirre Lehendakari etorb. 83, E48015 BILBAO, Spain. (email: javier.fernandezmacho at ehu.eus).
References
Fernández-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>