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NEWS.md
In WaveletComp: Computational Wavelet Analysis
Version 1.1 (18 March 2018)
Tools for displaying and analyzing periodic phenomena across time have been extended. The main innovations are:
* All functions of family wt.<> (showing results concerning a single time series) can now also be applied to extract univariate outcomes from cross-wavelet and coherence analysis (objects of class "analyze.coherency").
* It is possible to control the color gradation of time-period spectrum plots, and accentuate the contrast, by raising the wavelet power values to any (positive) exponent before plotting.
* Setting a maximum level for the color bar facilitates the visual comparison of time-period spectrum plots. Maximum and minimum plot levels are options for plots of averages too.
* The time and period axes are now easier to individualize by specifying tick marks and labels. Coordinates on the time axis can be conveniently addressed via an index or a POSIXct object.
* Graphical parameters of global coverage (cex.axis, font.axis, cex.lab, font.lab, mgp etc., see par) as well as parameters of local coverage (within axis specification options) help fine-tune plots.
* Two more real-world data sets have been included in WaveletComp, namely:
o Data set weather.radiation.Mannheim, containing daily weather and ambient radiation readings from Mannheim (Germany).
o Data set USelection2016.Instagram, containing hourly numbers of candidate-related media uploads to Instagram right before the 2016 US presidential election.
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WaveletComp documentation built on May 2, 2019, 6:33 a.m.
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Version 1.1 (18 March 2018)
Tools for displaying and analyzing periodic phenomena across time have been extended. The main innovations are: * All functions of family wt.<> (showing results concerning a single time series) can now also be applied to extract univariate outcomes from cross-wavelet and coherence analysis (objects of class "analyze.coherency"). * It is possible to control the color gradation of time-period spectrum plots, and accentuate the contrast, by raising the wavelet power values to any (positive) exponent before plotting. * Setting a maximum level for the color bar facilitates the visual comparison of time-period spectrum plots. Maximum and minimum plot levels are options for plots of averages too. * The time and period axes are now easier to individualize by specifying tick marks and labels. Coordinates on the time axis can be conveniently addressed via an index or a POSIXct object. * Graphical parameters of global coverage (cex.axis, font.axis, cex.lab, font.lab, mgp etc., see par) as well as parameters of local coverage (within axis specification options) help fine-tune plots. * Two more real-world data sets have been included in WaveletComp, namely: o Data set weather.radiation.Mannheim, containing daily weather and ambient radiation readings from Mannheim (Germany). o Data set USelection2016.Instagram, containing hourly numbers of candidate-related media uploads to Instagram right before the 2016 US presidential election.
Try the WaveletComp package in your browser
Any scripts or data that you put into this service are public.
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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