plot_wave.local.multiple.cross.regression: Auxiliary routine for plotting wave local multiple...

In jfdezmacho/wavemulcor: Wavelet Routines for Global and Local Multiple Regression and Correlation

Description

Produces a set of plots of wave local multiple cross-regressions.

Usage

plot_wave.local.multiple.cross.regression(Lst, lmax, nsig=2, 
     xaxt="s", pdf.write=NULL)

Arguments

Lst	A list from wave.multiplecross.regression.
lmax	maximum lag (and lead).
nsig	An optional value for the number of significant variables to plot_ Default is 2.
xaxt	An optional vector of labels for the "x" axis. Default is 1:n.
pdf.write	Optional name leader to save files to pdf format. The actual filename of each page "plot_<pdf.write>_WLMCC_<j>.pdf", where "j" is the wavelet level j=1...(J+1).

Details

The routine produces J+1 pages, one per wavelet level, each with time series plots of wave multiple cross-regressions at different lags and leads, each with their confidence interval. Also, the name of the variable that maximizes that multiple correlation against the rest is shown on top. The others are named with their order of significance when they are relevant.

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>

jfdezmacho/wavemulcor documentation built on Sept. 8, 2021, 1:51 a.m.