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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 |
| 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 |
| Reference manual: | spectral.pdf |
| 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 imports: | oreo |
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