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.
Maintainer: Tatsushi Oka oka.econ@gmail.com
Other contributors:
Heejon Han [contributor]
Oliver Linton [contributor]
Yoon-Jae Whang [contributor]
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.
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.