% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/xi_ccf.R
\name{xi_ccf}
\alias{xi_ccf}
\title{Bivariate Xi-Cross-Correlation Function}
\usage{
xi_ccf(
  x,
  y,
  max_lag = 20,
  n_surr = 399,
  sig_level = 0.05,
  max_iter = 100,
  direction = c("both", "x_leads"),
  ...
)
}
\arguments{
\item{x}{A numeric vector representing the first time series.}

\item{y}{A numeric vector representing the second time series.}

\item{max_lag}{An integer specifying the maximum lag to compute. Default is 20.}

\item{n_surr}{An integer specifying the number of MIAAFT surrogate datasets. Default is 399.}

\item{sig_level}{A numeric value specifying the significance level (FWER). Default is 0.05.}

\item{max_iter}{An integer specifying the maximum iterations for the MIAAFT algorithm. Default is 100.}

\item{direction}{A character string specifying the testing direction.
"both" computes X->Y and Y->X. "x_leads" computes only X->Y. Default is "both".}

\item{...}{Additional arguments.}
}
\value{
An S3 object of class \code{xi_ccf}.
}
\description{
Computes the directional Chatterjee's Xi coefficient between two time series
across multiple lags, with Family-Wise Error Rate (FWER) control.
}
