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.

Version:	0.1.1
Depends:	R (≥ 2.10)
Imports:	lpridge
Suggests:	dplyr, ggplot2, spelling, testthat (≥ 3.0.0)
Published:	2023-11-07
DOI:	10.32614/CRAN.package.timevarcorr
Author:	Alexandre Courtiol [aut, cre, cph], François Rousset [aut]
Maintainer:	Alexandre Courtiol <alexandre.courtiol at gmail.com>
BugReports:	https://github.com/courtiol/timevarcorr/issues
License:	MIT + file LICENSE
URL:	https://courtiol.github.io/timevarcorr/, https://github.com/courtiol/timevarcorr
NeedsCompilation:	no
Language:	en-US
Materials:	README NEWS
CRAN checks:	timevarcorr results

Documentation:

Reference manual:

timevarcorr.pdf

Downloads:

Package source:	timevarcorr_0.1.1.tar.gz
Windows binaries:	r-devel: timevarcorr_0.1.1.zip, r-release: timevarcorr_0.1.1.zip, r-oldrel: timevarcorr_0.1.1.zip
macOS binaries:	r-release (arm64): timevarcorr_0.1.1.tgz, r-oldrel (arm64): timevarcorr_0.1.1.tgz, r-release (x86_64): timevarcorr_0.1.1.tgz, r-oldrel (x86_64): timevarcorr_0.1.1.tgz

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