% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/xi_rolling_ccf.R
\name{run_rolling_xi_ccf}
\alias{run_rolling_xi_ccf}
\title{Rolling Multivariate Xi-CCF Analysis}
\usage{
run_rolling_xi_ccf(
  x,
  y,
  time_index = NULL,
  window_size,
  step_size = 1,
  max_lag = 20,
  n_surr = 100,
  bidirectional = TRUE,
  sig_level = 0.95,
  n_cores = NULL,
  save_dir = NULL
)
}
\arguments{
\item{x}{A numeric vector representing the first time series (predictor/lead candidate).}

\item{y}{A numeric vector representing the second time series (response/lag candidate).}

\item{time_index}{Optional vector of timestamps (e.g., Date, POSIXct) corresponding to x and y.}

\item{window_size}{An integer specifying the size of the rolling window.}

\item{step_size}{An integer specifying the step size by which the window is shifted. Default is 1.}

\item{max_lag}{An integer specifying the maximum positive lag to compute.}

\item{n_surr}{An integer specifying the number of MIAAFT surrogate datasets for the null hypothesis test.}

\item{bidirectional}{Logical. If TRUE (default), computes both "X leads Y" and "Y leads X".}

\item{sig_level}{A numeric value specifying the significance level for the confidence intervals. Default is 0.95.}

\item{n_cores}{An integer specifying the number of cores for parallel execution. If \code{NULL}, runs sequentially.}

\item{save_dir}{A character string specifying the directory path to save intermediate window results as RDS files. If \code{NULL} (default), results are not saved to disk.}
}
\value{
A \code{data.frame} containing the rolling window results in a tidy long-format.
}
\description{
Performs a rolling window analysis using Chatterjee's Xi cross-correlation to assess
the time-varying non-linear lead-lag relationship between two time series.
}
