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 |
Reference manual: | quantilogram.pdf |
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: quantilogram_2.1.1.tgz, r-oldrel: quantilogram_2.1.1.tgz |
Old sources: | quantilogram archive |
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