Computes the Wavelet deconvolution estimate of a common signal present in multiple channels that have possible different levels of blur and long memory additive error.
mwaved is a set of functions that generalise the waved package for wavelet deconvolution in the Fourier domain. These generalisations are the following extensions:
The user is encouraged to view the embedded Shiny applet that showcases the mwaved pacakge and importantly lists the appropriate R commands to recreate the output given by Shiny applet. The embedded Shiny applet can be viewed as long as the user has the shiny package installed on their machine and then using R command
The code is also written with the use of the Rcpp package to help use the external C FFTW library to achieve speeds around 8-15 times faster than the usual WaveD package (comparing the performance of a single channel waved code to the same code in the mwaved package with various sample sizes). The relative performance improves as the sample size increases.
The package is being developed at http://github.com/jrwishart/mwaved and any bug reports, comments or suggestions are welcomed at http://github.com/jrwishart/issues
Optional source compilation instructions (currently only tested in Ubuntu, Slackware Linux and Windows 10)
sudo apt-get install libfftw3-dev. For Windows 8 this requires downloading the windows fftw3 binaries and adding the installed directories to your PATH.
install.packages('mwaved')from the R prompt or download the tarball and run
R CMD INSTALL mwaved_1.x.x.tar.gz(where x.x is replaced with the appropriate version name) from the linux terminal.
testthatfunction calls to be compatible with the new
testthatpackage. i.e. new
testthatversion is backwards incompatible.
requirecommands from the source code.
Suggests gridExtrain favour of leaner import of a few select functions from the
whichargument to plot.mWaveD method to specify certain plots to be output.
waveletCoefobjects. Standardises the plotting of such coefficients using the
multiprefix that handle Multichannel deconvolution using the WaveD paradigm.
mWaveDobjects created by the
waveletCoefobject with a
plotmethod to help ease plotting of wavelet coefficients.
makeprefix (including LIDAR, Doppler, Blocks, Bumps and Cusp).
blurSignalfunctions to help ease simulation.