Common methods of spectral data analysis for unevenly sampled data
Common methods of spectral data analysis for unevenly sampled data
Fourier and Hilbert transforms are utilized to perform several types of spectral analysis on the supplied data. Fragmented and irregularly spaced data can be processed in terms of Lomb-Scargle method. Both, FFT as well as LOMB methods take multivariate data. A user friendly interface helps to interpret the results.
Keywords: Lomb-Scargle; Fourier, Hilbert, R
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Software in external data repository
Publication year 2019
Programming language: R
System requirements: PC, Windows, Linux, MAC
License: GPL-2
Permalink: https://www.hzdr.de/publications/Publ-29280