Extracting Signals from Wavelet Spectra
Add a wavelet plot
Add a plot of a the average spectral power of a continous wavelet tran...
Conduct the continuous wavelet transform on a time series/signal
Convert a proxy record to the time domain using anchor points
Anchor proxy record to an astronomical solution
Complete the tracking of cycle in a wavelet spectra
Convert a tracked tracked to a sedimentation rate curve
Convert the tracked curve to a depth time space
Convert the re-tracked curve results to a depth time space with uncert...
Anchor an age model including its uncertainty to a single radiometric ...
Convert data from the depth to the time domain
Remove tracking points which were tracked in a wavelet spectra
calculate the duration of stratigraphic gaps using astronomical cycles
Extract amplitude from a signal
Extract power from a wavelet spectra
Extract power from a wavelet spectra by using a constant period/durati...
Extract signal from a wavelet spectra using a traced period curve
Extract a signal/cycle from a wavelet spectra using a set period and b...
Extract signal from a wavelet spectrum using a upper and lower period ...
Extract a signal using standard deviation
Fit linear models to spectral peaks extracted from the wavelet spectra...
Generate standard color codes for the Geological Time Scale
Generates ages for the boundaries of a geochronological subdivision
Generate the mean age of a geological subdivision
Perform a Hilbert transform on a signal
Discriticizes lithologs
Perform an automatically loess based smoothing of a time series
Detect and filter out all maxima in a signal
Detect and filter out all minima in a signal
Create an age model using minimal tuning
Models average spectral power based curves based on a red-noise signal...
Calculate average spectral power from red noise curves for a given per...
Plot proxy record anchored to an astronomical solution
Plot the average spectral power of a wavelet spectra
Plot sedimentation modelling results
Plots a wavelet power spectra
Plot windowed fft based spectral analysis results
Re-track cycles using a Monte-Carlo simulation
Use a sedimentation curve to convert data to the time domain
Calculate sum of maximum spectral power for sedimentation rates for a ...
Track the period of a cycle in a wavelet spectra
Calculate the uncertainty associated with the wavelet analysis based o...
Extracting Signals from Wavelet Spectra
Example data sets for the 'WaverideR' package
Windowed fft based spectral analysis
The continuous wavelet transform enables the observation of transient/non-stationary cyclicity in time-series. The goal of cyclostratigraphic studies is to define frequency/period in the depth/time domain. By conducting the continuous wavelet transform on cyclostratigraphic data series one can observe and extract cyclic signals/signatures from signals. These results can then be visualized and interpreted enabling one to identify/interpret cyclicity in the geological record, which can be used to construct astrochronological age-models and identify and interpret cyclicity in past and present climate systems. The 'WaverideR' R package builds upon existing literature and existing codebase. The list of articles which are relevant can be grouped in four subjects; cyclostratigraphic data analysis,example data sets,the (continuous) wavelet transform and astronomical solutions. References for the cyclostratigraphic data analysis articles are: Stephen Meyers (2019) <doi:10.1016/j.earscirev.2018.11.015>. Mingsong Li, Linda Hinnov, Lee Kump (2019) <doi:10.1016/j.cageo.2019.02.011> Stephen Meyers (2012)<doi:10.1029/2012PA002307> Mingsong Li, Lee R. Kump, Linda A. Hinnov, Michael E. Mann (2018) <doi:10.1016/j.epsl.2018.08.041>. Wouters, S., Crucifix, M., Sinnesael, M., Da Silva, A.C., Zeeden, C., Zivanovic, M., Boulvain, F., Devleeschouwer, X. (2022) <doi:10.1016/j.earscirev.2021.103894>. Wouters, S., Da Silva, A.-C., Boulvain, F., and Devleeschouwer, X. (2021) <doi:10.32614/RJ-2021-039>. Huang, Norden E., Zhaohua Wu, Steven R. Long, Kenneth C. Arnold, Xianyao Chen, and Karin Blank (2009) <doi:10.1142/S1793536909000096>. Cleveland, W. S. (1979)<doi:10.1080/01621459.1979.10481038> Hurvich, C.M., Simonoff, J.S., and Tsai, C.L. (1998) <doi:10.1111/1467-9868.00125>, Golub, G., Heath, M. and Wahba, G. (1979) <doi:10.2307/1268518>. References for the example data articles are: Damien Pas, Linda Hinnov, James E. (Jed) Day, Kenneth Kodama, Matthias Sinnesael, Wei Liu (2018) <doi:10.1016/j.epsl.2018.02.010>. Steinhilber, Friedhelm, Abreu, Jacksiel, Beer, Juerg , Brunner, Irene, Christl, Marcus, Fischer, Hubertus, HeikkilA, U., Kubik, Peter, Mann, Mathias, Mccracken, K. , Miller, Heinrich, Miyahara, Hiroko, Oerter, Hans , Wilhelms, Frank. (2012 <doi:10.1073/pnas.1118965109>. Christian Zeeden, Frederik Hilgen, Thomas Westerhold, Lucas Lourens, Ursula Röhl, Torsten Bickert (2013) <doi:10.1016/j.palaeo.2012.11.009>. References for the (continuous) wavelet transform articles are: Morlet, Jean, Georges Arens, Eliane Fourgeau, and Dominique Glard (1982a) <doi:10.1190/1.1441328>. J. Morlet, G. Arens, E. Fourgeau, D. Giard (1982b) <doi:10.1190/1.1441329>. Torrence, C., and G. P. Compo (1998)<https://paos.colorado.edu/research/wavelets/bams_79_01_0061.pdf>, Gouhier TC, Grinsted A, Simko V (2021) <https://github.com/tgouhier/biwavelet>. Angi Roesch and Harald Schmidbauer (2018) <https://CRAN.R-project.org/package=WaveletComp>. Russell, Brian, and Jiajun Han (2016)<https://www.crewes.org/Documents/ResearchReports/2016/CRR201668.pdf>. Gabor, Dennis (1946) <http://genesis.eecg.toronto.edu/gabor1946.pdf>. J. Laskar, P. Robutel, F. Joutel, M. Gastineau, A.C.M. Correia, and B. Levrard, B. (2004) <doi:10.1051/0004-6361:20041335>. Laskar, J., Fienga, A., Gastineau, M., Manche, H. (2011a) <doi:10.1051/0004-6361/201116836>. References for the astronomical solutions articles are: Laskar, J., Gastineau, M., Delisle, J.-B., Farres, A., Fienga, A. (2011b <doi:10.1051/0004-6361/201117504>. J. Laskar (2019) <doi:10.1016/B978-0-12-824360-2.00004-8>. Zeebe, Richard E (2017) <doi:10.3847/1538-3881/aa8cce>. Zeebe, R. E. and Lourens, L. J. (2019) <doi:10.1016/j.epsl.2022.117595>. Richard E. Zeebe Lucas J. Lourens (2022) <doi:10.1126/science.aax0612>.