quantilogram-package {quantilogram} | R Documentation |
Quantilogram Analysis Tools
Description
This package provides a comprehensive set of tools for quantilogram analysis in R. It includes functions for computing and visualizing cross-quantilograms, which are useful for analyzing dependence structures in financial time series data. The package implements methods described in Han et al. (2016) for measuring quantile dependence and testing directional predictability between time series.
Details
The package's functions can be categorized into several groups:
Core Quantilogram Functions:
-
crossq
: Compute basic cross-quantilogram -
crossq.sb
: Cross-quantilogram with stationary bootstrap -
crossq.sb.opt
: Optimized cross-quantilogram with bootstrap
Visualization Functions:
-
crossq.heatmap
: Create heatmap visualization of cross-quantilograms -
crossq.plot
: Plot method for crossq objects
Advanced Analysis Functions:
-
crossq.max
: Compute maximum cross-quantilogram -
crossq.partial
: Compute partial cross-quantilogram
For a complete list of functions, see the package index.
Author(s)
Maintainer: Tatsushi Oka oka.econ@gmail.com
Other contributors:
Heejon Han [contributor]
Oliver Linton [contributor]
Yoon-Jae Whang [contributor]
References
Han, H., Linton, O., Oka, T., & Whang, Y. J. (2016). The cross-quantilogram: Measuring quantile dependence and testing directional predictability between time series. Journal of Econometrics, 193(1), 251-270.