Add to ORKG18 p.Here we present some preliminary results of a statistical–computational implementation to estimate the wavelet spectrum of unevenly spaced paleoclimate time series by means of the Morlet Weighted Wavelet Z-Transform (MWWZ). A statistical significance test is performed against an ensemble of first-order auto-regressive models (AR1) by means of Monte Carlo simulations. In order to demonstrate the capabilities of this implementation, we apply it to the oxygen isotope ratio (?18O) data of the GISP2 deep ice core (Greenland)
Reliable estimation of long-range dependence parameters is vital in time series. For example, in env...
We used detrended methods for scaling analysis (DFA2 and DMA) and wavelet transform spectral analysi...
The wavelet local multiple correlation (WLMC) is introduced for the first time in the study of clima...
Here we propose a permutation test-a non-parametric computing-intensive test-to evaluate the statist...
Wavelet analysis offers an alternative to Fourier based time-series analysis, and is particularly us...
Geophysical time series are sometimes sampled irregularly along the time axis. The situation is part...
The complexity of climate variability on all time scales requires the use of several refined tools t...
In nature, non-stationarity is rather typical, but the number of statistical tools allowing for non-...
Aiming to describe spatio-temporal climate variability on decadal-to-centennial time scales and long...
Aiming to describe spatio-temporal climate variability on decadal-to-centennial time scales and long...
International audienceIn this work, the continuous wavelet transform (CWT) is used to analyse stable...
Recent measurements of Earth's temperature have indicated a warming trend, and understanding the rol...
We propose two preprocessing algorithms suitable for climate time series. The first algorithm detec...
International audienceClimate variability is triggered by several solar and orbital cycles as well a...
[1] Do the chronological methods used in the construction of paleoclimate records influence the resu...
Reliable estimation of long-range dependence parameters is vital in time series. For example, in env...
We used detrended methods for scaling analysis (DFA2 and DMA) and wavelet transform spectral analysi...
The wavelet local multiple correlation (WLMC) is introduced for the first time in the study of clima...
Here we propose a permutation test-a non-parametric computing-intensive test-to evaluate the statist...
Wavelet analysis offers an alternative to Fourier based time-series analysis, and is particularly us...
Geophysical time series are sometimes sampled irregularly along the time axis. The situation is part...
The complexity of climate variability on all time scales requires the use of several refined tools t...
In nature, non-stationarity is rather typical, but the number of statistical tools allowing for non-...
Aiming to describe spatio-temporal climate variability on decadal-to-centennial time scales and long...
Aiming to describe spatio-temporal climate variability on decadal-to-centennial time scales and long...
International audienceIn this work, the continuous wavelet transform (CWT) is used to analyse stable...
Recent measurements of Earth's temperature have indicated a warming trend, and understanding the rol...
We propose two preprocessing algorithms suitable for climate time series. The first algorithm detec...
International audienceClimate variability is triggered by several solar and orbital cycles as well a...
[1] Do the chronological methods used in the construction of paleoclimate records influence the resu...
Reliable estimation of long-range dependence parameters is vital in time series. For example, in env...
We used detrended methods for scaling analysis (DFA2 and DMA) and wavelet transform spectral analysi...
The wavelet local multiple correlation (WLMC) is introduced for the first time in the study of clima...