quantilogram: Cross-Quantilogram

Estimation and inference methods for the cross-quantilogram. The cross-quantilogram is a measure of nonlinear dependence between two variables, based on either unconditional or conditional quantile functions. The cross-quantilogram can be considered as an extension of the correlogram, which is a correlation function over multiple lag periods and mainly focuses on linear dependency. One can use the cross-quantilogram to detect the presence of directional predictability from one time series to another. This package provides a statistical inference method based on the stationary bootstrap. See Linton and Whang (2007) <doi:10.1016/j.jeconom.2007.01.004> for univariate time series analysis and Han, Linton, Oka and Whang (2016) <doi:10.1016/j.jeconom.2016.03.001> for multivariate time series analysis.

Version: 2.1.1
Depends: R (≥ 2.10)
Imports: quantreg, SparseM, stats, np
Published: 2020-06-19
Author: Tatsushi Oka [aut, cre], Heejon Han [ctb], Oliver Linton [ctb], Yoon-Jae Whang [ctb]
Maintainer: Tatsushi Oka <oka.econ at gmail.com>
License: GPL-3
NeedsCompilation: no
Materials: README NEWS
CRAN checks: quantilogram results

Documentation:

Reference manual: quantilogram.pdf

Downloads:

Package source: quantilogram_2.1.1.tar.gz
Windows binaries: r-devel: quantilogram_2.1.1.zip, r-release: quantilogram_2.1.1.zip, r-oldrel: quantilogram_2.1.1.zip
macOS binaries: r-release (arm64): quantilogram_2.1.1.tgz, r-release (x86_64): quantilogram_2.1.1.tgz, r-oldrel: quantilogram_2.1.1.tgz
Old sources: quantilogram archive

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