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timevarcorr  

Time Varying Correlation
View on CRAN: Click here


Download and install timevarcorr package within the R console
Install from CRAN:
install.packages("timevarcorr")

Install from Github:
library("remotes")
install_github("cran/timevarcorr")

Install by package version:
library("remotes")
install_version("timevarcorr", "0.1.1")



Attach the package and use:
library("timevarcorr")
Maintained by
Alexandre Courtiol
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-11-07
Latest Update: 2023-11-07
Description:
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.
How to cite:
Alexandre Courtiol (2023). timevarcorr: Time Varying Correlation. R package version 0.1.1, https://cran.r-project.org/web/packages/timevarcorr. Accessed 18 Sep. 2026.
Previous versions and publish date:
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Other R packages that timevarcorr depends, imports, suggests or enhances
Complete documentation for timevarcorr
Functions, R codes and Examples using the timevarcorr R package
Some associated functions: CI . dot-onAttach . in_pkgdown . kern_smooth . stockprice . tcor . test_equality . test_ref . 
Some associated R codes: CI.R . data.R . smoothers.R . tcor.R . ttest.R . zzz.R .  Full timevarcorr package functions and examples
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