% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/xi_acf.R
\name{xi_acf}
\alias{xi_acf}
\alias{print.xi_acf}
\title{Compute empirical Xi-ACF and its significance via IAAFT surrogates}
\usage{
xi_acf(x, max_lag = 10, n_surr = 399, sig_level = 0.05, max_iter = 100, ...)

\method{print}{xi_acf}(x, ...)
}
\arguments{
\item{x}{A numeric vector representing the time series data. Must not contain missing values (NA) or be a constant.}

\item{max_lag}{An integer specifying the maximum lag to compute. Default is 10.}

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

\item{sig_level}{A numeric value between 0 and 1 specifying the significance level. Default is 0.05.}

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

\item{...}{Additional arguments (currently ignored).}
}
\value{
An object of class \code{xi_acf} containing the empirical ACF,
  pointwise thresholds, global threshold, and metadata.
}
\description{
Compute empirical Xi-ACF and its significance via IAAFT surrogates
}
