% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/crossq.R
\name{crossq}
\alias{crossq}
\title{Cross-Quantilogram}
\usage{
crossq(DATA, vecA, k)
}
\arguments{
\item{DATA}{An input matrix of dimensions T x 2, where T is the number of observations.
Column 1 contains the first variable and Column 2 contains the second variable.
This function will apply a k-period lag to the second variable during computation.}

\item{vecA}{A pair of two probability values at which sample quantiles are estimated}

\item{k}{A lag order (integer)}
}
\value{
Cross-Quantilogram
}
\description{
Returns the cross-quantilogram
}
\details{
This function obtains the cross-quantilogram at the k lag order.
}
\examples{
## data source 
data("sys.risk") 

## data: 2 variables 
D = sys.risk[,c("Market", "JPM")]

# probability levels for the 2 variables 
vecA = c(0.1, 0.5)

## cross-quantilogram with the lag of 5
crossq(D, vecA, 5)

}
\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." \emph{Journal of Econometrics}, 193(1), 251-270.
}
\author{
Heejoon Han, Oliver Linton, Tatsushi Oka and Yoon-Jae Whang
}
