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:Martin Seilmayer

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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'))

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

16 exports 1.80 score 5 dependencies 1 dependents 6 mentions 34 scripts 347 downloads

Last updated 3 years agofrom:b1219fce37. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 16 2024
R-4.5-winOKSep 16 2024
R-4.5-linuxOKSep 16 2024
R-4.4-winOKSep 16 2024
R-4.4-macOKSep 16 2024
R-4.3-winOKSep 16 2024
R-4.3-macOKSep 16 2024

Exports:amaxanalyticFunctionBPdeconvolveenvelopefilter.fftfilter.lombHinterpolate.fftspec.fftspec.lombwaterfallwin.coswin.hannwin.nuttwin.tukey

Dependencies:latticepbapplyplotrixrasterImageRhpcBLASctl