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

spectral_2.0.tar.gz
spectral_2.0.zip(r-4.7-any)spectral_2.0.zip(r-4.6-any)spectral_2.0.zip(r-4.5-any)
spectral_2.0.tgz(r-4.6-any)spectral_2.0.tgz(r-4.5-any)
spectral_2.0.tar.gz(r-4.7-any)spectral_2.0.tar.gz(r-4.6-any)
spectral_2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
spectral/json (API)

# Install 'spectral' in R:
install.packages('spectral', repos = c('https://seil85.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

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

3.29 score 2 packages 54 scripts 405 downloads 6 mentions 16 exports 5 dependencies

Last updated from:b1219fce37. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK95
source / vignettesOK194
linux-releaseOK106
macos-releaseOK138
macos-oldrelOK133
windows-develOK72
windows-releaseOK74
windows-oldrelOK69
wasm-releaseOK78

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

Dependencies:latticepbapplyplotrixrasterImageRhpcBLASctl