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Returns the partial cross-quantilogram
crossq.partial(DATA, vecA, k)The partial corss-quantilogram and the cross-quantilogram
A matrix
A vector of probability values at which sample quantiles are estiamted
The lag order
Heejoon Han, Oliver Linton, Tatsushi Oka and Yoon-Jae Whang
This function obtains the partial corss-quantilogram and the cross-quantilogram. To obtain the partial cross-correlation given an input matrix, this function interacts the values of the first column and the k-lagged values of the rest of the matrix.
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.
## 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 the lag of 5
crossq.max.partial(D, vecA, 5)
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