spectral: Common Methods of Spectral Data Analysis

On discrete data spectral analysis is performed by Fourier and Hilbert transforms as well as with model based analysis called Lomb-Scargle method. Fragmented and irregularly spaced data can be processed in almost all methods. Both, FFT as well as LOMB methods take multivariate data and return standardized PSD. For didactic reasons an analytical approach for deconvolution of noise spectra and sampling function is provided. A user friendly interface helps to interpret the results.

Version:	2.0
Depends:	rasterImage, lattice, RhpcBLASctl, pbapply, R (≥ 3.5.0)
Published:	2021-03-29
DOI:	10.32614/CRAN.package.spectral
Author:	Martin Seilmayer
Maintainer:	Martin Seilmayer <martin.seilmayer at gmail.com>
License:	GPL-2
NeedsCompilation:	no
Materials:	NEWS
In views:	TimeSeries
CRAN checks:	spectral results

Documentation:

Reference manual:

spectral.html , spectral.pdf

Downloads:

Package source:	spectral_2.0.tar.gz
Windows binaries:	r-devel: spectral_2.0.zip, r-release: spectral_2.0.zip, r-oldrel: spectral_2.0.zip
macOS binaries:	r-release (arm64): spectral_2.0.tgz, r-oldrel (arm64): spectral_2.0.tgz, r-release (x86_64): spectral_2.0.tgz, r-oldrel (x86_64): spectral_2.0.tgz
Old sources:	spectral archive

Reverse dependencies:

Reverse imports:

oreo

Linking:

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