plot_local.multiple.cross.correlation: Auxiliary routine for plotting local multiple...

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

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>

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