Package: spectral 2.0
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.
Authors:
spectral_2.0.tar.gz
spectral_2.0.zip(r-4.5)spectral_2.0.zip(r-4.4)spectral_2.0.zip(r-4.3)
spectral_2.0.tgz(r-4.4-any)spectral_2.0.tgz(r-4.3-any)
spectral_2.0.tar.gz(r-4.5-noble)spectral_2.0.tar.gz(r-4.4-noble)
spectral_2.0.tgz(r-4.4-emscripten)spectral_2.0.tgz(r-4.3-emscripten)
spectral.pdf |spectral.html✨
spectral/json (API)
NEWS
| # Install 'spectral' in R: |
| install.packages('spectral', repos = c('https://seil85.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 4 years agofrom:b1219fce37. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 15 2024 |
| R-4.5-win | OK | Nov 15 2024 |
| R-4.5-linux | OK | Nov 15 2024 |
| R-4.4-win | OK | Nov 15 2024 |
| R-4.4-mac | OK | Nov 15 2024 |
| R-4.3-win | OK | Nov 15 2024 |
| R-4.3-mac | OK | Nov 15 2024 |
Exports:amaxanalyticFunctionBPdeconvolveenvelopefilter.fftfilter.lombHinterpolate.fftspec.fftspec.lombwaterfallwin.coswin.hannwin.nuttwin.tukey
Dependencies:latticepbapplyplotrixrasterImageRhpcBLASctl
