wc.angle: Plot arrows into a cross-wavelet or wavelet coherency...

In WaveletComp: Computational Wavelet Analysis

Description

It adds arrows as symbolic indicators of phase-differences into a cross-wavelet spectrum or wavelet coherency spectrum of two time series.

In particular, the area to be filled with arrows can be determined in several ways: to reflect significance (at a given level) with respect to cross-wavelet power, wavelet coherency, or individual wavelet power, and/or to flag a high-value region ("high" according to a given level) with respect to cross-wavelet power (coherency values, respectively).

There is an option to choose "smoothed" arrows (phase differences) for plotting; these have been computed from smoothing filters as defined in analyze.coherency.

The name and layout were inspired by a similar function developed by Huidong Tian and Bernard Cazelles (archived R package WaveletCo). The code for the arrow design to reflect phase differences has been adopted from Huidong Tian.

Usage

wc.angle(WC = WC, exponent = 1, use.sAngle = TRUE, p = 1, 
         which.lvl = "wp", lvl = 0, 
         which.sig = which.lvl, siglvl = 0.05, 
         col.arrow = "black")

Arguments

WC	an object of class analyze.coherency

exponent	Exponent applied to cross-wavelet power (or wavelet coherence, depending on which.lvl) values before selecting the area to be filled with arrows according to level, see lvl (only effective if p = 0 or p = 2); the exponent should be positive. Default: 1.
use.sAngle	Use smoothed version of phase difference to plot arrows? Logical. Default: FALSE.

p

Which area should be filled with arrows displaying phase differences? [0 :] Select the area w.r.t. power (or coherence, depending on which.lvl. The value of lvl is the threshold. Set lvl = 0 to plot arrows over the entire area. [1 :] Select the area w.r.t. significance as specified in which.sig. The value of siglvl is the threshold. [2 :] Intersection of both areas above. Default: 1.

which.lvl	Which spectrum should be used to restrict the area of arrows according to its level? "wp" : cross-wavelet power "wc" : wavelet coherence Default: "wp".
lvl	minimum level of cross-wavelet power (or wavelet coherence, depending on which.lvl) for arrows to be plotted (only effective if p = 0 or p = 2). Default: 0.

which.sig	Which spectrum and corresponding p-values should be used to restrict the area of arrows according to significance? "wp" : cross-wavelet power "wc" : wavelet coherence "wt" : individual wavelet power Default: which.lvl
siglvl	level of significance referring to which.sig (only effective if p = 1 or p = 2). Default: 0.05.

col.arrow

arrow color. Default: "black".

Author(s)

Angi Roesch and Harald Schmidbauer; credits are also due to Huidong Tian, and Bernard Cazelles.

References

Aguiar-Conraria L., and Soares M.J., 2011. Business cycle synchronization and the Euro: A wavelet analysis. Journal of Macroeconomics 33 (3), 477–489.

Aguiar-Conraria L., and Soares M.J., 2011. The Continuous Wavelet Transform: A Primer. NIPE Working Paper Series 16/2011.

Cazelles B., Chavez M., Berteaux, D., Menard F., Vik J.O., Jenouvrier S., and Stenseth N.C., 2008. Wavelet analysis of ecological time series. Oecologia 156, 287–304.

Liu P.C., 1994. Wavelet spectrum analysis and ocean wind waves. In: Foufoula-Georgiou E., and Kumar P., (eds.), Wavelets in Geophysics, Academic Press, San Diego, 151–166.

Tian, H., and Cazelles, B., 2012. WaveletCo. Available at https://cran.r-project.org/src/contrib/Archive/WaveletCo/, archived April 2013; accessed July 26, 2013.

Torrence C., and Compo G.P., 1998. A practical guide to wavelet analysis. Bulletin of the American Meteorological Society 79 (1), 61–78.

Veleda D., Montagne R., and Araujo M., 2012. Cross-Wavelet Bias Corrected by Normalizing Scales. Journal of Atmospheric and Oceanic Technology 29, 1401–1408.

See Also

analyze.coherency, wc.image, arrow

WaveletComp documentation built on May 2, 2019, 6:33 a.m.