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. It can be considered an extension of the correlogram,
which is a correlation function over multiple lag periods that 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. For detailed theoretical and
empirical explanations, see Linton and Whang (2007) for univariate
time series analysis and Han, Linton, Oka and Whang (2016) for
multivariate time series analysis. The full references for these key
publications are as follows: (1) Linton, O., and Whang, Y. J. (2007).
The quantilogram: with an application to evaluating directional
predictability. Journal of Econometrics, 141(1), 250-282
<doi:10.1016/j.jeconom.2007.01.004>; (2) Han, H., Linton, O., Oka, T.,
and Whang, Y. J. (2016). The cross-quantilogram: measuring quantile
dependence and testing directional predictability between time series.
Journal of Econometrics, 193(1), 251-270
<doi:10.1016/j.jeconom.2016.03.001>.
| Version: |
3.1.1 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
ggplot2, np, quantreg, rlang, scales, stats |
| Suggests: |
knitr, rmarkdown, SparseM |
| Published: |
2024-08-27 |
| DOI: |
10.32614/CRAN.package.quantilogram |
| 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 |
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