Learn R Programming

W2CWM2C (version 1.0)

W2CWM2C-package: 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) and the 'wave.multiple.correlation' and 'wave.multiple.cross.correlation' (Wavemulcor package).

Description

The W2CWM2C package improves the plots of the Wavelet (Cross) Correlation (bivariate case) from the waveleslim package (Whitcher 2012) and the Wavelet Multiple (Cross) Correlation (multivariate case) from the wavemulcor package (Fernandez-Macho 2012). 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.

Arguments

encoding

latin1

Details

ll{ Package: W2CWM2C Type: Package Version: 1.0 Date: 2012-10-15 License: GPL (>= 2) LazyLoad: yes } The W2CWM2C package contains four functions: the WC (that perform and plot the Wavelet correlation, bivariate case), the WCC (that perform and plot the Wavelet Cross Correlation, bivariate case), the WMC (that perform and plot the Wavelet Multiple Correlation, multivariate case) and the WMCC (that perform and plot the Wavelet Multiple Cross Correlation, multivariate case).

References

Fernandez-Macho, J.. 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, 2012. Fernandez-Macho, J. (2012). Wavemulcor Reference manual. The Comprehensive R Archive Network (CRAN), http://cran.r- project.org/web/packages/wavemulcor/index.html Gencay, R., F. Selcuk and B. Whitcher (2001) An Introduction to Wavelets and Other Filtering Methods in Finance and Economics, Academic Press. Polanco-Martinez, J. and J. Fernandez-Macho (2012). An empirical analysis of some peripheral EU stock market indices: A Wavelet cross-correlation approach. Under review Physica A: Statistical Mechanics and its Applications. (Manuscript Number: PHYSA-12867). Polanco-Martinez, J. and J. Fernandez-Macho (2012). The package 'W2CWM2C': description, features and applications. To be submitted under review to Journal of Statistical Software. Whitcher, B., P. Guttorp, and D.B. Percival. Wavelet analysis of covariance with application to atmospheric time series. Journal of Geophysical Research - Atmospheres, 105(D11):941-962, 2000. Whitcher, B. (2012). Waveslim reference manual. The Comprehensive R Archive Network (CRAN), http://cran.r-project.org/web/packages/waveslim/index.html