2020
DOI: 10.1007/s40435-020-00706-y
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Vector wavelet coherence for multiple time series

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Cited by 20 publications
(6 citation statements)
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“…Given this study’s time-dependency and non-stationarity of the dengue and climatic data, we recognized the need for a specialized clustering analysis approach. To address these challenges, we utilized a methodology based on vector wavelet coherence, introduced by Oygur and Unal [ 38 ]. This approach provides a means to assess the synchronicity and co-movements between various climatic time series and dengue data.…”
Section: Methodsmentioning
confidence: 99%
“…Given this study’s time-dependency and non-stationarity of the dengue and climatic data, we recognized the need for a specialized clustering analysis approach. To address these challenges, we utilized a methodology based on vector wavelet coherence, introduced by Oygur and Unal [ 38 ]. This approach provides a means to assess the synchronicity and co-movements between various climatic time series and dengue data.…”
Section: Methodsmentioning
confidence: 99%
“…We performed all analyses using R Statistical Software (R Core Team, 2021). We built linear regression models using nlme , forecast and orcutt packages and used the WaveletComp and vectorwavelet packages to conduct wavelet analyses (Bates et al, 2021; Hyndman et al, 2021; Oygur et al, 2021; Roesch & Schmidbauer, 2018; Stefano et al, 2018).…”
Section: Methodsmentioning
confidence: 99%
“…Multiple wavelet coherence was also conducted between EDFD, SMPD, and NINO3.4 time series indexes to further investigate the interaction with ENSO and severe FD. Multiple wavelet coherence can calculate a wavelet coherence with an n‐dimensional vector and also computes a continuous wavelet transform similar to biwavelet coherence (Oygur & Unal, 2020). Wavelet coherence(s) were performed using the R packages biwavelet and vectorwavelet with 50,000 and 10,000 Monte Carlo simulations respectively (Gouhier et al., 2021).…”
Section: Methodsmentioning
confidence: 99%