plot_wave.local.multiple.regression: Auxiliary routine for plotting wave local multiple...
In wavemulcor: Wavelet Routines for Global and Local Multiple Regression and Correlation
Description
Usage
Arguments
Details
Value
Author(s)
References
Description
Produces a set of plots of wave local multiple regressions.
Usage
1
plot_wave.local.multiple.regression(Lst,nsig=2, xaxt="s")
Arguments
Lst
A list from wave.multiple.regression.
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.
Details
The routine produces J+1 time series plots of wave multiple regressions, 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>
wavemulcor documentation built on Sept. 5, 2021, 5:56 p.m.
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Description Usage Arguments Details Value Author(s) References
Description
Produces a set of plots of wave local multiple regressions.
Usage
1 | plot_wave.local.multiple.regression(Lst,nsig=2, xaxt="s")
|
Arguments
Lst |
A list from wave.multiple.regression. |
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. |
Details
The routine produces J+1 time series plots of wave multiple regressions, 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>
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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