W2CWM2C-package: W2CWM2C: a graphical tool for wavelet (cross) correlation and...

In W2CWM2C: A Graphical Tool for Wavelet (Cross) Correlation and Wavelet Multiple (Cross) Correlation Analysis

Description

The W2CWM2C package is a set of functions that improves the graphical presentations of the functions 'wave.correlation' and 'spin.correlation' (wavelet cross correlation) (waveslim package, Whitcher 2012) and the 'wave.multiple.correlation' and 'wave.multiple.cross.correlation' (wavemulcor package, Fernandez-Macho 2012b). The plot outputs (heatmaps) can be displayed in the screen or can be saved as PNG or JPG images or as PDF or EPS formats. The W2CWM2C package also helps to handle the (input data) multivariate time series easily as a list of N elements (times series) and provides a multivariate data set (dataexample) to exemplify its use. A description of the package was published by Polanco-Martinez and Fernandez-Macho (2014), <doi:10.1109/MCSE.2014.96>.

Details

Package:	W2CWM2C
Type:	Package
Version:	2.2
Date:	2021-01-07
License:	GPL (>= 2)
LazyLoad:	yes

The W2CWM2C package contains four functions: (1) WC that performs and plots the wavelet correlation for the bivariate case, (2) WCC that performs and plots the wavelet cross correlation for the bivariate case, (3) WMC that performs and plots the wavelet multiple correlation for the multivariate case, and 4) WMCC that performs and plots the wavelet multiple cross correlation for the multivariate case.

Note

Dependencies: waveslim, wavemulcor and colorspace.

Author(s)

Josue M. Polanco-Martinez (a.k.a. jomopo).
BC3 - Basque Centre for Climate Change, Bilbao, Spain.
Web1: https://scholar.google.es/citations?user=8djLIhcAAAAJ&hl=en.
Web2: https://www.researchgate.net/profile/Josue_Polanco-Martinez.
Email: [e-mail]

Acknowledgement:
I am thankful to Jan de Leeuw and Achim Zeileis for suggesting the use of the R package colorspace. I am also thanks to Debojyoti Das, John Garrigan, Peterson Owusu Junior, Rim Ibrahim, and Ato Wilberforce for reporting some bugs found in my W2CWM2C package. The author acknowledges to the SEPE (Spanish Public Service of Employment) for its funding support.

References

Fernandez-Macho, J. (2012a). Wavelet multiple correlation and cross-correlation: A multiscale analysis of Euro zone stock markets. Physica A: Statistical Mechanics and its Applications,
391(4):1097–1104. doi: 10.1016/j.physa.2011.11.002.

Fernandez-Macho, J. (2012b). wavemulcor: Wavelet routine for multiple correlation. R package version 1.2, The Comprehensive R Archive Network (CRAN), <URL: https://cran.r-project.org/package=wavemulcor>.

Gencay, R., F. Selcuk and B. Whitcher (2001) An Introduction to Wavelets and Other Filtering Methods in Finance and Economics, Academic Press.

Ihaka, R., Murrell, P., Hornik, K., Fisher, J. C. and Zeileis, A. (2012). colorspace: Color Space Manipulation. R package version 1.2.0, The Comprehensive R Archive Network (CRAN), <URL: https://cran.r-project.org/package=colorspace>.

Polanco-Martinez, J. and J. Fernandez-Macho (2014). The package 'W2CWM2C': description, features and applications. Computing in Science & Engineering, 16(6):68–78.
doi: 10.1109/MCSE.2014.96.

Polanco-Martinez, J. M. and Abadie, L. M. (2016). Analyzing crude oil spot price dynamics versus long term future prices: A wavelet analysis approach. Energies, 9(12), 1089. doi: 10.3390/en9121089.

Whitcher, B., P. Guttorp, and D.B (2000). Percival. Wavelet analysis of covariance with application to atmospheric time series. Journal of Geophysical Research - Atmospheres, 105(D11):941–962. doi: 10.1029/2000JD900110.

Whitcher, B. (2012). waveslim: Basic wavelet routines for one-, two- and three-dimensional signal processing. R package version 1.7.1. The Comprehensive R Archive Network (CRAN),
<URL: https://cran.r-project.org/package=waveslim>.

Zeileis A, Hornik K, Murrell P (2009). Escaping RGBland: Selecting Colors for Statistical Graphics. Computational Statistics & Data Analysis, 53, 3259–3270. doi: 10.1016/j.csda.2008.11.033.

W2CWM2C documentation built on Jan. 13, 2021, 11:54 a.m.