timevarcorr
Time Varying Correlation
Computes how the correlation between 2 time-series changes over time. To do so, the package follows the method from Choi & Shin (2021) doi:10.1007/s42952-020-00073-6. It performs a non-parametric kernel smoothing (using a common bandwidth) of all underlying components required for the computation of a correlation coefficient (i.e., x, y, x^2, y^2, xy). An automatic selection procedure for the bandwidth parameter is implemented. Alternative kernels can be used (Epanechnikov, box and normal). Both Pearson and Spearman correlation coefficients can be estimated and change in correlation over time can be tested.
- Version0.1.1
- R versionunknown
- LicenseMIT
- LicenseLICENSE
- Needs compilation?No
- Languageen-US
- Last release11/07/2023
Documentation
Team
Alexandre Courtiol
MaintainerShow author detailsFrançois Rousset
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Insights
Last 30 days
This package has been downloaded 139 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 6 times.
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Last 365 days
This package has been downloaded 1,845 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Jan 21, 2025 with 25 downloads.
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Dependencies
- Imports1 package
- Suggests4 packages