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nonParQuantileCausality: Nonparametric Causality in Quantiles Test

Implements the nonparametric causality-in-quantiles test (in mean or variance), returning a test object with an S3 plot() method. The current implementation uses one lag of each series (first-order Granger causality setup). Methodology is based on Balcilar, Gupta, and Pierdzioch (2016a) <doi:10.1016/j.resourpol.2016.04.004> and Balcilar et al. (2016) <doi:10.1007/s11079-016-9388-x>.

Version: 0.1.0
Depends: R (≥ 3.6)
Imports: stats, ggplot2, quantreg, KernSmooth
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2025-09-30
DOI: 10.32614/CRAN.package.nonParQuantileCausality
Author: Mehmet Balcilar [aut, cre]
Maintainer: Mehmet Balcilar <mehmet at mbalcilar.net>
License: MIT + file LICENSE
URL: https://www.mbalcilar.net, https://github.com/mbalcilar/nonParQuantileCausality
NeedsCompilation: no
Citation: nonParQuantileCausality citation info
Materials: README, NEWS
CRAN checks: nonParQuantileCausality results

Documentation:

Reference manual: nonParQuantileCausality.html , nonParQuantileCausality.pdf
Vignettes: Getting started with nonParQuantileCausality (source, R code)

Downloads:

Package source: nonParQuantileCausality_0.1.0.tar.gz
Windows binaries: r-devel: nonParQuantileCausality_0.1.0.zip, r-release: nonParQuantileCausality_0.1.0.zip, r-oldrel: nonParQuantileCausality_0.1.0.zip
macOS binaries: r-release (arm64): nonParQuantileCausality_0.1.0.tgz, r-oldrel (arm64): not available, r-release (x86_64): nonParQuantileCausality_0.1.0.tgz, r-oldrel (x86_64): nonParQuantileCausality_0.1.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.