Package: wavemulcor
Title: Wavelet Routines for Global and Local Multiple Correlation
Version: 2.2.1
Authors@R: person("Javier", "Fernandez-Macho", email = "javier.fernandezmacho@ehu.es", role = c("aut", "cre"))
Description: Wavelet routines that calculate single sets of 
             wavelet multiple correlations (WMC) and cross-correlations (WMCC)
             out of n variables. 
             They can later be plotted in single graphs, as an alternative to trying 
             to make sense out of several sets of wavelet correlations or 
             wavelet cross-correlations. 
             The code is based on the calculation, at each wavelet scale, of the 
             square root of the coefficient of determination in a linear combination 
             of variables for which such coefficient of determination is a maximum. 
             The code provided here is based on the wave.correlation routine in 
             Brandon Whitcher's waveslim R package Version: 1.6.4, which in turn is 
             based on wavelet methodology developed in Percival and Walden (2000) <DOI:10.1017/CBO9780511841040>; 
             Gençay, Selçuk and Whitcher (2002) <DOI:10.1016/B978-012279670-8.50013-6> and others.
             Version 2 incorporates wavelet local multiple correlations (WLMC).
             These are like the previous global WMC but consisting in one
             single set of multiscale correlations along time. That is, at each time
             t, they are calculated by letting a window of weighted wavelet 
             coefficients around t move along time. Six weight functions are provided.
             Namely, the  uniform window, Cleveland's tricube window, Epanechnikov's 
             parabolic window, Bartlett's triangular window and Wendland's truncated 
             power window and the Gaussian window.
             Version 2.2 incorporates an auxiliary function that calculates local 
             multiple correlations (LMC). They are calculated by letting move along time 
             a window of weighted time series values around t. Any of the six weight 
             functions mentioned above can be used.
License: GPL (>= 2)
Depends: R (>= 3.4.0), waveslim (>= 1.7.5)
Suggests: plot3D
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-08 18:58:21 UTC; jf
Author: Javier Fernandez-Macho [aut, cre]
Maintainer: Javier Fernandez-Macho <javier.fernandezmacho@ehu.es>
Repository: CRAN
Date/Publication: 2018-06-08 21:32:58 UTC
