crossq.max.partial {quantilogram} | R Documentation |
Partial Corss-Quantilogram upto a given lag order
Description
The partial cross-quantilograms from 1 to a given lag order.
Usage
crossq.max.partial(DATA, vecA, Kmax)
Arguments
DATA |
An input matrix |
vecA |
A vector of probability values at which sample quantiles are estimated |
Kmax |
The maximum lag order (integer) |
Details
This function calculates the partial cross-quantilograms up to the lag order users specify.
Value
A vector of cross-quantilogram and a vector of partial cross-quantilograms
Author(s)
Heejoon Han, Oliver Linton, Tatsushi Oka and Yoon-Jae Whang
References
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.
Examples
## data source
data("sys.risk")
## data with 3 variables
D = sys.risk[,c("Market", "JPM", "VIX")]
## probablity levels for the 3 variables
vecA = c(0.1, 0.1, 0.1)
## partial cross-quantilogram with lags from 1 to 5
crossq.max.partial(D, vecA, 5)
[Package quantilogram version 2.2.1 Index]