Common Methods of Spectral Data Analysis
Overview
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.
- add summary() and print() functions
- add deconvolve() function to perform analytically deconvolution
- add standardized PSD and false alarm probability to spec.fft-function
- spec.fft handles NA-values by zero padding and simple energy recovery.
- enhance calculation speed by multithreaded BLAS (must be replaced by user)
- add 1D FFT interpolation function
- read out cache size for memory usage in spec.lomb
- bug fix memory calculation in spec.lomb()
- bug fix single frequency in spec.lomb()
- optional cluster (hpc) calculation in spec.lomb()
- adding a progressbar to spec.lomb()
- waterfall() calculates PSD as well
Show all changes in 2.0Hide the rest of the changes in 2.0
- changed variable band width in waterfall()
- waterfall also ignores NA values and corrects
- adding progress bar to waterfall()
- extending band pass function BP() by sinc, bi-cubic and gauss kernels
- modified all dependend functions which use band pass BP()
- add Hanning window function
From NEWS in the release
Install
Health
NOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Maintainer: ‘Martin Seilmayer <martin.seilmayer@gmail.com>’
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Authors@R: person(given = "Martin",
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as necessary.- NOTE11 OK, 2 NOTE2026-06-08
- ERROR11 OK, 1 NOTE, 1 ERROR2026-06-07
- NOTE12 OK, 2 NOTE2026-03-10
Documentation
- Help pages
- 27
- Examples that run
- 60%9 run in a plain check · 6 hold no code
- Exported functions with examples
- 50%
- Documented parameters
- 100%
- Return-value docs
- 69%
- Help pages citing references
- 11%
Downloads
Dependencies
Installing spectral adds 4 packages (1 with compiled code, 383 KB of source tarballs). Heaviest: plotrix 313 KB, RhpcBLASctl 41 KB, pbapply 23 KB.
Code & Tests
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- 2.0Latest2021-03-29 · current release · diff ↗ ·
added 6 exports
BP, amax, deconvolve, interpolate.fft, win.hann, win.nutt - RR 4.0.0 released · 2020-04-24
- 1.32019-06-03 · diff ↗
- RR 3.6.0 released · 2019-04-26
- RR 3.5.0 released · 2018-04-23
- RR 3.4.0 released · 2017-04-21
- 1.0.12016-09-15 · diff ↗
- 1.02016-09-13
- RR 3.3.0 released · 2016-05-03
Package metadata
- First published
- 2016-09-13
- Total releases
- 4 / 10 yrs
- License
- GPL-2 OSI
- Minimum R
- ≥ 3.5.0
- Download size
- 49 KB
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