The least-squares wavelet analysis (LSWA) is a robust method of analyzing any type of time/data series without the need for editing and preprocessing of the original series. The LSWA can rigorously analyze any non-stationary and equally/unequally spaced series with an associated covariance matrix that may have trends and/or datum shifts. The least-squares cross-wavelet analysis complements the LSWA in the study of the coherency and phase differences of two series of any type. A MATLAB software package including a graphical user interface is developed for these methods to aid researchers in analyzing pairs of series. The package also includes the least-squares spectral analysis, the antileakage least-squares spectral analysis, and the least-squares cross-spectral analysis to further help researchers study the components of interest in a series. We demonstrate the steps that users need to take for a successful analysis using three examples: two synthetic time series, and a Global Positioning System time series.

LSWAVE. A MATLAB software for the least-squares wavelet and cross-wavelet analyses / Ghaderpour, E.; Pagiatakis, S. D.. - In: GPS SOLUTIONS. - ISSN 1080-5370. - 23:2(2019). [10.1007/s10291-019-0841-3]

LSWAVE. A MATLAB software for the least-squares wavelet and cross-wavelet analyses

Ghaderpour E.
Primo
Writing – Original Draft Preparation
;
2019

Abstract

The least-squares wavelet analysis (LSWA) is a robust method of analyzing any type of time/data series without the need for editing and preprocessing of the original series. The LSWA can rigorously analyze any non-stationary and equally/unequally spaced series with an associated covariance matrix that may have trends and/or datum shifts. The least-squares cross-wavelet analysis complements the LSWA in the study of the coherency and phase differences of two series of any type. A MATLAB software package including a graphical user interface is developed for these methods to aid researchers in analyzing pairs of series. The package also includes the least-squares spectral analysis, the antileakage least-squares spectral analysis, and the least-squares cross-spectral analysis to further help researchers study the components of interest in a series. We demonstrate the steps that users need to take for a successful analysis using three examples: two synthetic time series, and a Global Positioning System time series.
2019
Antileakage least-squares spectral analysis; GPS time series analysis; Least-squares cross-spectral analysis; Least-squares cross-wavelet analysis; Least-squares spectral analysis; Least-squares wavelet analysis
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LSWAVE. A MATLAB software for the least-squares wavelet and cross-wavelet analyses / Ghaderpour, E.; Pagiatakis, S. D.. - In: GPS SOLUTIONS. - ISSN 1080-5370. - 23:2(2019). [10.1007/s10291-019-0841-3]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1655312
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